# Gigasheet — how to use (mcp.ai)

Connect your Gigasheet account and use 150 tools for spreadsheets straight from your AI agent. Connect with your own API key. Gigasheet is a big data automation platform that offers a spreadsheet-like interface for analyzing and managing large datasets, enabling users to automate tasks, integrate with various data sources, and streamline data workflows.

## Option A — via MCP (recommended)
Remote MCP endpoint (HTTP, streamable): `https://api.mcp.ai/p_gigasheet?ms=1787293620000`
Add it as a custom/remote MCP connector in your client (Claude, Cursor, VS Code…), then authenticate when prompted. Once connected, ask the agent to use the server's tools (e.g. `gigasheet_append_dataset`).

## Option B — via direct REST API
Base URL: `https://api.mcp.ai/api/gigasheet`
Auth: `Authorization: Bearer sk_live_…` — create a workspace API key at https://mcp.ai/settings/api-keys
Discover endpoints: `GET https://api.mcp.ai/api/gigasheet/_endpoints`

### Endpoints
- `POST https://api.mcp.ai/api/gigasheet/append/dataset` — Appends rows to an existing Gigasheet dataset using column letters as keys. Use when you need to add new data rows to a sheet by specifying values for each column position (A, B, C, etc.).
  - body: { handle: string, records: object[] }
- `POST https://api.mcp.ai/api/gigasheet/append/dataset/from/sheet` — Tool to append data from a source sheet to a target sheet by matching column names. Use when you need to combine data from two existing sheets based on column name matching rather than column IDs. Thi
  - body: { handle: string, from_handle: string, case_insensitive?: boolean, trim_column_names?: boolean, add_unmatched_columns?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/apply/user/defined/http/enrichment` — Tool to apply generic HTTP enrichment to a Gigasheet dataset. Use when you need to enrich dataset rows by calling external APIs and adding the response data as new columns. This action creates an enri
  - body: { bulk?: object, handle: string, method: string, columns: object[], headers?: object, recipe_id?: string, sort_model?: object[], filter_model?: object, url_template: string, LaxValidation?: boolean, body_template?: string, response_type?: string, output_path_map: object[], retry_properties?: object, body_escape_format?: string, email_on_completion?: string[], maximum_requests_per_second?: number }
- `POST https://api.mcp.ai/api/gigasheet/calculate/enrich/expected/credits` — Calculate expected credits for a user-defined HTTP enrichment operation. Use this before initiating an enrichment to estimate costs based on the number of rows and columns that will be processed. This
  - body: { colIds?: string[], handle: string, filterModel?: object }
- `POST https://api.mcp.ai/api/gigasheet/cancel/enrich/user/defined/http/task` — Tool to cancel a running enrichment task. Use when you need to stop an in-progress HTTP enrichment job that was previously initiated. This action attempts to cancel an enrichment task identified by it
  - body: { task_handle: string }
- `POST https://api.mcp.ai/api/gigasheet/check/connectors/sources/connectorname` — Tool to check if a source of the given type is available. Use this to verify whether a specific connector integration (e.g., Snowflake, Salesforce) is configured and available for the authenticated us
  - body: { connector_name: string }
- `POST https://api.mcp.ai/api/gigasheet/combine/files` — Tool to combine multiple files into a new file. Use when you need to merge several files where column names and types match. Optionally add source filename tracking or append rows to the first file in
  - body: { handles: string[], inPlace?: boolean, fileName?: string, folderHandle?: string, addInputFilename?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/copy/file` — Tool to copy a file in Gigasheet. Use when you need to duplicate an existing file/sheet into your library with an optional new name and destination folder.
  - body: { state?: object, handle: string, fileName?: string, recursive?: boolean, folderHandle?: string }
- `POST https://api.mcp.ai/api/gigasheet/count/dataset/deduplicate/rows` — Tool to count how many duplicates will be removed and how many rows remain when deduplicating. Use when you need to preview the impact of a deduplication operation before executing it, or to understan
  - body: { handle: string, columns?: string[], sortModel?: object[], filterModel?: object }
- `POST https://api.mcp.ai/api/gigasheet/count/dataset/groups` — Tool to count the number of groups matching certain criteria in a Gigasheet dataset. Use when you need to determine how many distinct groups exist based on specified row grouping columns and optional 
  - body: { endRow?: integer, handle: string, startRow?: integer, groupKeys?: string[], pivotCols?: object[], pivotMode?: boolean, sortModel?: object[], valueCols?: object[], FieldTypes?: string[], filterModel?: object, rowGroupCols: object[], AllowUnstableOrder?: boolean, ungroupedAggregations?: object[] }
- `POST https://api.mcp.ai/api/gigasheet/count/dataset/rows` — Counts rows in a Gigasheet dataset matching specified filter criteria. Returns the number of rows matching the provided filters, groupings, and other parameters. For basic row counting, only the handl
  - body: { endRow?: integer, handle: string, startRow?: integer, groupKeys?: string|integer|number|boolean[], pivotCols?: object[], pivotMode?: boolean, sortModel?: object[], valueCols?: object[], FieldTypes?: string[], filterModel?: object, rowGroupCols?: object[], AllowUnstableOrder?: boolean, ungroupedAggregations?: object[] }
- `POST https://api.mcp.ai/api/gigasheet/count/datasets/activity/count` — Tool to get total activity count on a given Gigasheet dataset. Use when you need to determine how many activities (creates, updates, deletes) have been performed on a dataset. This action counts activ
  - body: { End?: string, Page?: integer, Query?: string, Start?: string, Users?: string[], handle: string, Actions?: string[], PageSize?: integer, Categories?: string[] }
- `POST https://api.mcp.ai/api/gigasheet/create/ai/chat` — AI analysis assistant for Gigasheet datasets. Use this to ask natural language questions about sheet data and get AI-powered insights. Only available for sheets where you have write permissions. Commo
  - body: { Query: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/create/dataset/column/comment` — Tool to add a comment to a column in a Gigasheet dataset. Use this when you need to annotate or document a specific column with explanatory text. Optionally notify other users by tagging their email a
  - body: { column: string, handle: string, comment: string, tagged_emails?: string[], share_with_tagged_emails?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/create/dataset/comment` — Tool to add a comment to a specific cell in a Gigasheet dataset. Use when you need to annotate or add notes to a particular cell location in the sheet.
  - body: { row: integer, column: string, handle: string, comment: string, tagged_emails?: string[], share_with_tagged_emails?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/create/dataset/conditional/label/column` — Tool to add a label column to a Gigasheet dataset with values based on conditional filters. Use when you need to categorize or label rows based on column values. This action creates a new column where
  - body: { cases: object[], handle: string, defaultLabel?: string, outputColumn: string }
- `POST https://api.mcp.ai/api/gigasheet/create/dataset/formula` — Tool to create a new column based on a formula input in a Gigasheet dataset. Use when you need to calculate values based on existing columns. This action creates a new column with values computed from
  - body: { handle: string, formula?: string, columnName: string, afterColumnId?: string, literalFormula?: string }
- `POST https://api.mcp.ai/api/gigasheet/create/dataset/formula/edit` — Tool to edit a formula column in a Gigasheet dataset. Use when you need to update an existing formula column with a new formula, rename it, or reposition it. The column must already exist and be a for
  - body: { column: string, handle: string, formula?: string, columnName?: string, afterColumnId?: string, literalFormula?: string }
- `POST https://api.mcp.ai/api/gigasheet/create/dataset/formula/preview` — Tool to calculate a formula preview on a Gigasheet dataset and return sample results with involved column values. Use this action when you need to: - Test a formula expression before applying it to an
  - body: { handle: string, formula: string }
- `POST https://api.mcp.ai/api/gigasheet/create/dataset/iterator/column` — Tool to add an iterator column to a Gigasheet dataset based on current filters and order. Use when you need sequential row numbers in your data. This action creates a new column with sequential number
  - body: { handle: string, sortModel?: object[], columnName: string, filterModel?: object }
- `POST https://api.mcp.ai/api/gigasheet/create/dataset/liveshare` — Tool to create a new liveshare for a Gigasheet dataset. Returns a share ID and URL for accessing the current CSV data in the sheet. Use when you need to generate a shareable link that provides live ac
  - body: { handle: string, client_state_version_id?: string }
- `POST https://api.mcp.ai/api/gigasheet/create/dataset/view` — Tool to create a new view for a Gigasheet dataset with a specified name and client state version. Use when you need to save a specific dataset state as a named view for later reference.
  - body: { name: string, handle: string, client_state_id: string }
- `POST https://api.mcp.ai/api/gigasheet/create/explode/json` — Tool to explode JSON data in a column into separate columns. Extracts all keys from JSON objects and creates a new column for each key. Use when you need to flatten nested JSON data in a Gigasheet dat
  - body: { keys?: string[], column: string, handle: string, indices?: integer[] }
- `POST https://api.mcp.ai/api/gigasheet/create/file/aggregation` — Tool to retrieve ungrouped aggregated values for a Gigasheet file. Returns aggregated data as specified in the request payload, including support for pivot mode, filtering, sorting, and various aggreg
  - body: { endRow?: integer, handle: string, startRow?: integer, groupKeys?: string[], pivotCols?: object[], pivotMode?: boolean, sortModel?: object[], valueCols?: object[], FieldTypes?: string[], filterModel?: object, rowGroupCols?: object[], AllowUnstableOrder?: boolean, ungroupedAggregations?: object[] }
- `POST https://api.mcp.ai/api/gigasheet/create/files/blank` — Tool to create an empty file in your Gigasheet Library. Use when you need a blank spreadsheet with a specified number of rows and columns.
  - body: { numCols: integer, numRows: integer, filename: string, folderHandle?: string, uploadToTeam?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/create/files/directory` — Tool to create a new folder in your Gigasheet Library. Use when you need to organize datasets by creating a new directory for file storage.
  - body: { name: string }
- `POST https://api.mcp.ai/api/gigasheet/create/lookup` — Creates a cross-file lookup to enrich data by matching values between two sheets. Use when you need to pull related data from a reference sheet into your source sheet based on matching column values. 
  - body: { col: string, handle: string, referenceFile: object, matchConditions?: object, returnAllMatches?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/create/mcp` — Tool to interact with Gigasheet Sheet Assistant via the Model Context Protocol (MCP) over HTTP. Use when you need to query or manipulate sheet data through MCP-compatible LLM tools. This endpoint impl
  - body: { id: integer|string, method: string, params: object, jsonrpc: string }
- `POST https://api.mcp.ai/api/gigasheet/create/split/column` — Tool to split a column into multiple columns based on a separator. Use when you need to divide column values into separate columns in a Gigasheet dataset.
  - body: { Column: string, handle: string, Separator: string }
- `POST https://api.mcp.ai/api/gigasheet/delete/ai/handle/logs` — Tool to delete Sheet Assistant chat history for a specific sheet. Use when you need to clear all AI assistant conversation logs associated with a sheet handle.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/delete/columns/by/name` — Tool to delete multiple columns from a Gigasheet dataset by their column names. Use when you need to remove specific columns from a sheet.
  - body: { handle: string, column_names: string[] }
- `POST https://api.mcp.ai/api/gigasheet/delete/connectors/sources/connectorname` — Tool to delete a connector source for the authenticated user. Use when you need to remove an integration connection such as Salesforce, S3, or Google Sheets from Gigasheet.
  - body: { connector_name: string }
- `POST https://api.mcp.ai/api/gigasheet/delete/dataset/comment` — Tool to delete a comment from a cell in a Gigasheet dataset. Use this when you need to remove a specific comment that was previously added to a cell. The comment ID can be obtained using the list comm
  - body: { row: integer, column: string, handle: string, comment: string }
- `POST https://api.mcp.ai/api/gigasheet/delete/dataset/delete/rows/not/matching/filter` — Deletes rows in a Gigasheet dataset that do NOT match the specified filter criteria. Use this when you want to keep only the rows that match a filter and remove everything else. The filter uses Conjun
  - body: { handle: string, filterModel: object }
- `POST https://api.mcp.ai/api/gigasheet/delete/dataset/handle/deduplicate/rows` — Tool to delete duplicated rows from a Gigasheet dataset based on specified columns and sort model. Use when you need to remove duplicate entries identified by matching values in one or more columns. W
  - body: { handle: string, columns: string[], sortModel?: object[], filterModel?: object }
- `POST https://api.mcp.ai/api/gigasheet/delete/dataset/handle/delete/rows` — Tool to delete selected rows from a Gigasheet dataset. Use when you need to remove specific rows identified by their row IDs (iterator numbers). Row IDs are subject to change, so it's best practice to
  - body: { rows: integer[], handle: string }
- `POST https://api.mcp.ai/api/gigasheet/delete/dataset/handle/delete/rows/matching/filter` — Tool to delete rows in a Gigasheet dataset that match a specified filter. Use when you need to remove specific rows based on filter criteria. The filterModel uses Conjunctive Normal Form (CNF) structu
  - body: { handle: string, filterModel: object }
- `POST https://api.mcp.ai/api/gigasheet/delete/dataset/handle/views/view` — Tool to delete a specific view from a Gigasheet dataset. Use when you need to remove a saved view from a dataset. Requires both the dataset handle and the view handle to identify the view to delete.
  - body: { view: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/delete/dataset/liveshare/shareid` — Tool to delete a live share of a Gigasheet dataset. Use when you need to revoke or remove an existing live share link. The shareid is the unique identifier of the live share to be deleted.
  - body: { shareid: string }
- `POST https://api.mcp.ai/api/gigasheet/delete/delete/handle` — Deletes a Gigasheet sheet or folder by its unique handle identifier. For sheets, this permanently removes the dataset. For folders, use recursive=True to delete the folder along with all its contents 
  - body: { handle: string, recursive?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/delete/files/columns/column` — Tool to delete a single column from a Gigasheet sheet by its column identifier. Use when you need to permanently remove a specific column from a sheet.
  - body: { column: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/delete/filter/templates/filter/handle` — Tool to delete a saved filter template by its unique handle. Use when you need to remove a persisted filter configuration that is no longer needed.
  - body: { filter_handle: string }
- `POST https://api.mcp.ai/api/gigasheet/delete/multiple/columns` — Tool to delete multiple columns from a Gigasheet file. Use when you need to remove specific columns from a sheet by their identifiers.
  - body: { handle: string, columnsToDelete: string[] }
- `POST https://api.mcp.ai/api/gigasheet/filter/file/rows` — Tool to retrieve rows from a Gigasheet file matching specified filter criteria. Use when you need to query or extract data from a sheet with optional filtering, sorting, and pagination. For basic filt
  - body: { endRow?: integer, handle: string, startRow?: integer, groupKeys?: string|integer|number|boolean[], pivotCols?: object[], pivotMode?: boolean, sortModel?: object[], valueCols?: object[], FieldTypes?: string[], filterModel?: object, rowGroupCols?: object[], columnHighlights?: object, AllowUnstableOrder?: boolean, ungroupedAggregations?: object[] }
- `POST https://api.mcp.ai/api/gigasheet/generate/dataset/description` — Generates an AI-powered description for a Gigasheet dataset. Use this when you need to automatically create a summary or description of a dataset's content and structure based on its data.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/ai/handle/logs` — Tool to retrieve AI chat history for a sheet. Returns up to 20 most recent messages exchanged with the sheet assistant. Use when you need to review previous AI interactions or understand the conversat
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/cell/comments` — Tool to get comments for a specific cell in a Gigasheet dataset. Use when you need to retrieve comments that have been added to a particular cell at the intersection of a column and row.
  - body: { row: integer, column: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/client/state/current/version` — Retrieves the current client-state version and timestamp for a specified sheet. The version identifier is used when creating or updating views and saved states. Call this action after obtaining a shee
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/connector/connection/params` — Tool to get connection parameters for a specific connector. Use when you need to discover what parameters are required to set up a connector integration.
  - body: { connector_name: string }
- `POST https://api.mcp.ai/api/gigasheet/get/connectors/connection/params/connectorname` — Tool to retrieve connection parameters for a specific connector type. Use when you need to discover what parameters are required to configure a data source connection.
  - body: { connector_name: string }
- `POST https://api.mcp.ai/api/gigasheet/get/connectors/connections` — Tool to list connector connections. Use after setting a valid Gigasheet API token.
- `POST https://api.mcp.ai/api/gigasheet/get/connectors/sources` — Tool to retrieve information about connected data sources for the user. Returns a list of data sources with their type, status, and folder location. Use after setting a valid Gigasheet API token.
- `POST https://api.mcp.ai/api/gigasheet/get/connectors/sources/params/connectorname` — Tool to get parameters required for a specific connector source type. Use when configuring a data source connection to understand what information needs to be collected from the user.
  - body: { connector_name: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/column/comments` — Tool to get comments for a specific column in a dataset sheet. Use when you need to retrieve comments that have been added to a particular column.
  - body: { column: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/handle` — Retrieves comprehensive metadata for a specific dataset in Gigasheet. This tool fetches detailed information about a dataset including its processing status, file properties, column structure, owner i
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/handle/columns` — Tool to list all column metadata (IDs, names, types) for a dataset. Use after obtaining a dataset handle.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/handle/download/export` — Tool to retrieve the download URL for an exported dataset. Use after initiating an export and obtaining its handle.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/handle/liveshare/shareid` — Tool to retrieve CSV data from a Gigasheet liveshare. Returns the current data in text CSV format. Use when you need to export or access shared dataset data via a liveshare link.
  - body: { handle: string, shareid: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/handle/note` — Tool to retrieve a dataset's note by handle. Use this to get AI-generated or user-provided descriptions of a dataset.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/handle/organization/permissions` — Tool to retrieve organization file permissions for a dataset. Use when you need to check what permissions the requester's organization has on a specific file. This action returns permissions only for 
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/handle/version` — Retrieves metadata about a dataset at a specific version. Returns information including file name, column names and types, row count, modification timestamp, and processing status. Use this when you n
  - body: { handle: string, version: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/handle/views` — Tool to list all views associated with a specific dataset. Use after confirming the dataset handle and its status.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/operation/status` — Tool to get information about the last operation on a dataset. Use when you need to check if a long-running operation (like import, export, or data transformation) has completed.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/dataset/views` — Tool to retrieve view metadata for a specific view within a dataset. Use when you have both a dataset handle and a view handle to get detailed view information.
  - body: { view: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/datasets/handle/activity` — Tool to get the list of write actions on a given dataset sheet. Use this to retrieve the activity history and audit trail of modifications made to a dataset.
  - body: { page?: string, handle: string, pageSize?: string }
- `POST https://api.mcp.ai/api/gigasheet/get/docs/formulas/functions` — Tool to retrieve all supported formula functions. Use after authenticating with a valid API token.
  - body: { accept?: string, flatten?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/get/enrich/user/defined/http/task/handle` — Tool to get status for a user-defined HTTP enrichment task. Use when you need to check if an enrichment operation has completed or to monitor its progress.
  - body: { task_handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/filter/template/on/sheet` — Tool to fetch a saved filter template's model for a given sheet. Use when you need the exact filter structure for a specific sheet and template.
  - body: { handle: string, filter_handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/filter/templates` — Retrieves all saved filter templates from GigaSheet. Filter templates store reusable filter configurations that can be applied to datasets. Returns a list of templates with their IDs, names, owners, f
  - body: { page?: integer }
- `POST https://api.mcp.ai/api/gigasheet/get/filter/templates/filter/handle` — Retrieves details of a specific saved filter template by its unique handle. Use when you need to inspect a particular filter template's configuration, metadata, or filter criteria.
  - body: { filter_handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/generate/handle` — Tool to generate a new unique dataset handle. Use when you need a fresh FileUuid before creating or referencing datasets.
- `POST https://api.mcp.ai/api/gigasheet/get/library` — Tool to retrieve all datasets and files in the user's Gigasheet library. Returns all datasets owned by the user at any folder depth, files directly shared with the user, and IDs of files the user has 
- `POST https://api.mcp.ai/api/gigasheet/get/library/handle` — Retrieves all library files with file permissions in a given directory. Returns library files owned by the user making the request, limited to the requested directory level only (does not include nest
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/library/home` — Tool to retrieve suggested recent files for the home page. Returns a list of recently accessed datasets with metadata, permissions, and sharing information. Use when you need to display or work with t
- `POST https://api.mcp.ai/api/gigasheet/get/library/path` — Tool to retrieve the chain of parent directories for a file or folder in Gigasheet. Returns the complete path hierarchy from root to the specified item, sorted by folder level. Use when you need to un
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/get/ticintel/npi/npi/public` — Tool to retrieve public NPI (National Provider Identifier) profile from TICIntel database. Use when you need comprehensive information about a healthcare provider including their specialty, location, 
  - body: { npi: string }
- `POST https://api.mcp.ai/api/gigasheet/get/ticintel/states` — Tool to list available TIC Intel states from Gigasheet. Returns a list of state names or codes that can be used for TIC Intel data queries. Use when you need to know which states are available for TIC
- `POST https://api.mcp.ai/api/gigasheet/get/ticintel/states/state/cities` — Tool to retrieve a list of cities for a given US state code from the TICIntel dataset. Use when you need to get all available cities within a specific state.
  - body: { state: string }
- `POST https://api.mcp.ai/api/gigasheet/get/ticintel/states/state/cities/city/providers` — Tool to retrieve a list of healthcare providers in a specific city and state from the TicIntel dataset. Use when you need to find providers by geographic location.
  - body: { city: string, state: string }
- `POST https://api.mcp.ai/api/gigasheet/get/user/details` — Retrieves detailed information about the authenticated user in Gigasheet. Use when you need to check user account details, storage quota usage, or verify assigned roles and permissions.
- `POST https://api.mcp.ai/api/gigasheet/get/user/enrichment/credits` — Tool to get the current user's enrichment credit information. Use when you need to check available enrichment credits or usage.
- `POST https://api.mcp.ai/api/gigasheet/get/user/metadata` — Tool to retrieve metadata for the authenticated user. Returns user metadata including billing info, feature flags, and onboarding status. Use when you need to fetch user configuration or settings.
- `POST https://api.mcp.ai/api/gigasheet/get/user/space/used` — Tool to get the amount of space used by the current user in bytes. Use when you need to check storage usage.
- `POST https://api.mcp.ai/api/gigasheet/get/user/whoami` — Tool to fetch the authenticated user's details. Use after setting a valid Gigasheet API token.
- `POST https://api.mcp.ai/api/gigasheet/get/users/autofill` — Retrieves autofill suggestions for the authenticated user, including team members and previously used share recipients. Useful for autocomplete functionality when sharing files or collaborating with t
  - body: { filters?: object }
- `POST https://api.mcp.ai/api/gigasheet/list/billing/plans` — Tool to list available Gigasheet billing plans. Returns all billing plans with their item details and pricing information. Use when you need to view subscription options.
- `POST https://api.mcp.ai/api/gigasheet/list/dataset/comments` — Tool to get all comments in a dataset sheet. Use this when you need to retrieve comments that have been added to cells in the dataset.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/list/dataset/liveshares` — Tool to list all liveshares for a specific Gigasheet dataset. Use when you need to view existing shared links for a dataset.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/list/datasets` — Tool to retrieve all datasets owned by the user at any folder depth. Returns a list of datasets with their metadata. The API may trim certain fields to keep response size manageable. Use the 'types' p
  - body: { types?: string[] }
- `POST https://api.mcp.ai/api/gigasheet/list/datasets/by/handle` — Tool to list files and datasets in a given Gigasheet location. Use when you need to browse the contents of a parent dataset or folder, optionally filtering by type (sheet or export). Supports paginati
  - body: { page?: integer, types?: string[], handle: string, pageSize?: integer }
- `POST https://api.mcp.ai/api/gigasheet/list/library/exports` — Tool to list exports owned by the current user, regardless of location. Use when you need to retrieve all exports associated with the authenticated user's account.
  - body: { page?: integer, pageSize?: integer }
- `POST https://api.mcp.ai/api/gigasheet/list/shared/files/by/handle` — Tool to retrieve all files with permissions shared with the user in a specific directory location. Use when you need to see what files have been shared with you in a particular folder. Returns files l
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/move/file/directory` — Tool to move a file or folder into a folder or to the root of your Library. Use when organizing your Gigasheet workspace. The destination folder must already exist, and creating directory loops is for
  - body: { handle: string, dest_dir_handle?: string }
- `POST https://api.mcp.ai/api/gigasheet/patch/user/metadata` — Tool to update user metadata in Gigasheet. Use this to modify user-level settings such as billing integration (Chargebee ID), feature flags (pre-analysis), and onboarding state. At least one field mus
  - body: { userEmail?: string, onboarding?: object, chargebee_id?: string, feature_preanalysis?: string }
- `POST https://api.mcp.ai/api/gigasheet/post/ai/handle/formulate` — Tool to generate Excel-style formulas using AI based on natural language queries. Use when you need to create formulas for data transformation, calculation, or extraction on a Gigasheet dataset. This 
  - body: { Query: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/cast/column/handle/column` — Tool to change a column's data type in a Gigasheet dataset. Use when you need to convert column data from one type to another (e.g., string to number, text to IP address). The operation is asynchronou
  - body: { column: string, handle: string, cast_type: string, cast_format: string }
- `POST https://api.mcp.ai/api/gigasheet/post/change/case/handle/col` — Tool to change the case of a column to Uppercase, Lowercase, Capitalized, or Proper. Use when you need to standardize text formatting in a column for consistency or data processing requirements.
  - body: { col: string, case: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/clean/company/name/handle/col` — Tool to clean company names by stripping common business suffixes (Inc., LLC, Corp., etc.). Use when standardizing company names to avoid duplicates. Currently works only on English-alphabet versions 
  - body: { col: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/combine/columns/handle` — Tool to combine multiple columns into a single new column with a separator. Use when you need to merge column values from a Gigasheet dataset.
  - body: { name: string, handle: string, columns: string[], separator: string }
- `POST https://api.mcp.ai/api/gigasheet/post/dataset/handle/append/by/name` — Appends one or more rows to a Gigasheet dataset using column names as keys. This tool adds new rows to an existing dataset by matching the keys in each record to the column names in the sheet. Column 
  - body: { handle: string, records: object[] }
- `POST https://api.mcp.ai/api/gigasheet/post/dataset/handle/assistant/tips` — Tool to generate AI-powered tips for analyzing a dataset. Use when you need suggestions for data analysis or exploration. This action generates intelligent recommendations based on the dataset structu
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/dataset/handle/export` — Initiates an asynchronous export job for a Gigasheet dataset. Returns an export job handle that can be used with the download export endpoint to retrieve the exported file once processing completes. U
  - body: { handle: string, gridState?: object }
- `POST https://api.mcp.ai/api/gigasheet/post/dataset/handle/find/and/replace` — Tool to find and replace values in specified columns of a Gigasheet dataset. Use when you need to update or clean data by replacing specific values across one or more columns. This action creates a ne
  - body: { find: string, colIDs: string[], handle: string, replace: string, language?: string, caseSensitive?: boolean, wholeCellMatch?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/post/dataset/handle/insert/blank/row` — Tool to insert a blank row with null values into a dataset. Use after determining the insertion index.
  - body: { index: integer, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/dataset/handle/rename/columns/to/unique` — Tool to rename all columns in a dataset to unique names. Use when duplicate column names could cause conflicts in downstream processing.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/dataset/handle/save/current/view` — Saves the current view state of a Gigasheet dataset and returns a view handle. This operation captures the current layout, filters, sorts, column visibility, and other view settings of the dataset at 
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/dataset/handle/select/columns/by/name` — Tool to select specific columns from a Gigasheet dataset by name, keeping only those columns in the specified order. Use when you need to reduce a dataset to only certain columns or reorder columns. A
  - body: { handle: string, column_names: string[] }
- `POST https://api.mcp.ai/api/gigasheet/post/extract/domain/handle/col` — Tool to extract domain from a URL column in a Gigasheet dataset. Use when you need to parse URLs and extract just the domain portion (e.g., extracting 'example.com' from 'https://www.example.com/path'
  - body: { col: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/file/handle/filter/by/name` — Filter rows in a Gigasheet file by column names and return matching results. This endpoint uses column names directly (not column IDs) and supports text, number, and date filters. Use this when you ne
  - body: { endRow?: integer, handle: string, startRow?: integer, filterModel: object }
- `POST https://api.mcp.ai/api/gigasheet/post/file/handle/filter/sheet/row/nr` — Maps an unfiltered row number to its position in the filtered result set. Returns the 1-based index of where a specific row appears after filters are applied, or 0 if the row is filtered out. Useful f
  - body: { handle: string, row_nr: integer }
- `POST https://api.mcp.ai/api/gigasheet/post/file/handle/filter/stream/progress` — Filter data from a Gigasheet file with real-time streaming progress updates. Returns filtered rows along with processing statistics (bytes and rows processed). Use when you need to apply filters to a 
  - body: { endRow?: integer, handle: string, startRow?: integer, groupKeys?: string|integer[], pivotCols?: object[], pivotMode?: boolean, sortModel?: object[], valueCols?: object[], FieldTypes?: string[], filterModel?: object, rowGroupCols?: object[], columnHighlights?: object, AllowUnstableOrder?: boolean, ungroupedAggregations?: object[] }
- `POST https://api.mcp.ai/api/gigasheet/post/file/handle/save/exported` — Saves a file state with applied filters and grouping to create an exported version. Returns a JSON response acknowledging if the save request was successful. Use this action when you need to persist f
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/files/combine/by/name` — Tool to combine multiple files by a shared column name. Use when you need to merge several Gigasheet files based on a common header.
  - body: { columnName: string, outputName?: string, fileHandles: string[] }
- `POST https://api.mcp.ai/api/gigasheet/post/maven/export` — Tool to export Gigasheet data to AWS S3. Use after generating an export handle and ensuring the S3 bucket has correct permissions.
  - body: { params: object, connector: string, exportHandle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/maven/import` — Tool to import data from AWS S3 into your Gigasheet Library. Use when you need to pull objects or prefixes from an S3 bucket into Gigasheet.
  - body: { params: object, connector: string }
- `POST https://api.mcp.ai/api/gigasheet/post/request/access/handle` — Tool to request access to a Gigasheet file. Use when you need permission to view or edit a file owned by another user.
  - body: { handle: string, message?: string }
- `POST https://api.mcp.ai/api/gigasheet/post/request/api/access` — Request API access by sending a notification to Gigasheet support team. This tool sends a notification email to Gigasheet support requesting API key access for the authenticated user. The Gigasheet te
- `POST https://api.mcp.ai/api/gigasheet/post/trim/whitespace/handle/col` — Tool to trim leading and trailing whitespace from all values in a column. Use when you need to clean up text data and remove extra spaces for consistency and data quality.
  - body: { col: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/post/unroll/delimited/column/handle/column` — Tool to explode a column containing delimited data into multiple rows. Use after confirming dataset handle and target column.
  - body: { column: string, handle: string, splitBy?: string }
- `POST https://api.mcp.ai/api/gigasheet/post/upload/direct` — Tool to upload raw data directly to Gigasheet using byte array contents. Use when you have file data as bytes and want to create a new sheet or append to an existing one.
  - body: { name: string, contents: integer[], callbackUrl?: string, targetHandle?: string, parentDirectory?: string, skipNotification?: boolean, skipTypeInference?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/post/upload/url` — Tool to upload data to Gigasheet from a specified URL. Use when you have a public or pre-signed link and want to ingest it directly.
  - body: { url: string, name?: string }
- `POST https://api.mcp.ai/api/gigasheet/preview/enrich/user/defined/http` — Tool to preview a generic HTTP enrichment on a Gigasheet dataset before executing it on all rows. This action tests the HTTP enrichment configuration by executing a small sample of requests and return
  - body: { bulk?: object, handle: string, method: string, columns: object[], headers?: object, recipe_id?: string, sort_model?: object[], filter_model?: object, url_template: string, LaxValidation?: boolean, body_template?: string, response_type?: string, output_path_map: object[], retry_properties?: object, body_escape_format?: string, email_on_completion?: string[], maximum_requests_per_second?: number }
- `POST https://api.mcp.ai/api/gigasheet/put/dataset/handle/clientstate/version` — Applies or restores a specific client state version to a dataset. Client state includes view settings like filters, sorts, visible columns, and aggregations. Use this to restore a previously saved sta
  - body: { handle: string, version: string }
- `POST https://api.mcp.ai/api/gigasheet/put/dataset/handle/col/row/by/name` — Tool to update a cell in a dataset by specifying column name and row number. Use after dataset is loaded and column name uniqueness is ensured.
  - body: { row: integer, value: string|integer|number|boolean, column: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/put/file/handle/share/file` — Tool to share a Gigasheet file with specified recipients. Use after creating or updating a sheet to grant email-based access.
  - body: { emails: string[], handle: string, message?: string, permissions: integer[] }
- `POST https://api.mcp.ai/api/gigasheet/put/file/handle/share/opt/out` — Tool to remove your access from a file that has been shared with you. Use when you want to opt out of a shared file.
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/put/filter/templates/filter/handle` — Tool to create or update a saved filter template. Use when you need to persist or modify filter criteria by providing a filter handle and the filter model.
  - body: { sheet: string, filter_model: object, filter_handle: string }
- `POST https://api.mcp.ai/api/gigasheet/rename/columns/by/name` — Tool to rename columns in a Gigasheet dataset using their current names. Use when you need to update column names to more descriptive or standardized values.
  - body: { handle: string, rename_columns: object[] }
- `POST https://api.mcp.ai/api/gigasheet/rename/file` — Tool to rename a file in Gigasheet. Use when you need to change the display name of a sheet.
  - body: { handle: string, filename: string }
- `POST https://api.mcp.ai/api/gigasheet/reset/client/state` — Resets the client state of a sheet to the default state. This clears all view customizations including filters, sorts, visible columns, and aggregations, returning the sheet to its original default vi
  - body: { handle: string }
- `POST https://api.mcp.ai/api/gigasheet/reset/user/password` — Tool to trigger password reset for the authenticated user. Use when a user needs to reset their password and has a valid API token.
- `POST https://api.mcp.ai/api/gigasheet/search/datasets/activity` — Tool to search the history of write actions performed on a Gigasheet dataset. Use when you need to audit changes, track user activity, or review the modification history of a dataset. Returns a pagina
  - body: { End?: string, Page?: integer, Query?: string, Start?: string, Users?: string[], handle: string, Actions?: string[], PageSize?: integer, Categories?: string[] }
- `POST https://api.mcp.ai/api/gigasheet/search/library` — Tool to search through the Gigasheet file library by file metadata. Use when you need to find files by owner name, file name, column headers, or notes. By default searches across owner, file_name, hea
  - body: { fields?: string[], searchTerm: string }
- `POST https://api.mcp.ai/api/gigasheet/send/invite` — Tool to send email invitations to join Gigasheet. Use when you need to invite users to collaborate on the platform.
  - body: { recipients: string[] }
- `POST https://api.mcp.ai/api/gigasheet/set/client/state/aggregate/filter/model` — Tool to set the aggregate filter model in the client state of a sheet. Use this to apply aggregate filtering to your data view by providing the sheet handle and the filter model object.
  - body: { handle: string, filterModel: object }
- `POST https://api.mcp.ai/api/gigasheet/set/client/state/aggregations` — Sets aggregations in the client state of a sheet. Aggregations allow you to compute summary statistics (sum, count, average, min, max, etc.) across columns in your dataset. Use this action to define w
  - body: { handle: string, aggregations: object[] }
- `POST https://api.mcp.ai/api/gigasheet/set/client/state/column/state` — Tool to set column state in the client state of a sheet. Use to configure column widths, sort order, visibility, pinning, and aggregations. This updates the visual layout and behavior of columns in th
  - body: { handle: string, columnState: object[] }
- `POST https://api.mcp.ai/api/gigasheet/set/client/state/filter/model` — Tool to set the filter model in the client state of a sheet. Use when you need to apply or update filter conditions to a dataset's view state. Pass an empty object to clear all filters.
  - body: { handle: string, filterModel: object }
- `POST https://api.mcp.ai/api/gigasheet/set/client/state/group/columns` — Tool to set group columns in the client state of a sheet. Use this to configure which columns are used for grouping data in the sheet view. Column IDs must be letter-based (A, B, C) not numeric.
  - body: { handle: string, columnIds: string[] }
- `POST https://api.mcp.ai/api/gigasheet/set/client/state/sort/model` — Sets the sort model for a sheet's client state. Use this to programmatically sort data by one or more columns in ascending or descending order. The sort model persists as part of the sheet's view stat
  - body: { handle: string, sortModel: object[] }
- `POST https://api.mcp.ai/api/gigasheet/set/client/state/visible/columns` — Tool to set visible columns in the client state of a sheet. Use when you want to control which columns are displayed in the sheet view. If columnIds is empty, all columns will be shown.
  - body: { handle: string, columnIds?: string[] }
- `POST https://api.mcp.ai/api/gigasheet/set/dataset/clientstate` — Sets the client state of a dataset using a state object. Client state includes view settings like filters, sorts, visible columns, and aggregations. Use this to apply custom view configurations to a d
  - body: { state: object, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/set/dataset/column/currency` — Tool to set currency format for a dataset column. Use when you need to format numeric data as currency with specific currency codes.
  - body: { column: string, handle: string, currency_code: string }
- `POST https://api.mcp.ai/api/gigasheet/set/dataset/note` — Tool to set or update a note on a dataset in Gigasheet. Use this to add descriptive text, context, or metadata to a dataset for documentation purposes. The note can be up to 20,000 characters long and
  - body: { note: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/update/dataset/cell` — Tool to update a single cell value in a Gigasheet dataset by column letter and row number. Use after dataset is loaded and when you know the specific column letter (A, B, C, etc.) and row number to up
  - body: { col: string, row: string, value: string, handle: string }
- `POST https://api.mcp.ai/api/gigasheet/update/dataset/views` — Tool to update the client state of a specified view. Use when you need to rename a view or update its client state ID.
  - body: { name?: string, view: string, handle: string, client_state_id?: string }
- `POST https://api.mcp.ai/api/gigasheet/upsert/rows` — Tool to upsert rows in an existing Gigasheet dataset. Use when you need to insert or update multiple rows of data starting from a specific column and row position. Overlapping cells will be overwritte
  - body: { col: string, row: string, cells: string[][], handle: string }
- `POST https://api.mcp.ai/api/gigasheet/validate/dataset/formula` — Tool to validate a formula expression against a dataset. Use when you need to check if a formula is syntactically correct and can be applied to the dataset before executing it.
  - body: { handle: string, formula: string }
- `POST https://api.mcp.ai/api/gigasheet/validate/files/combine` — Tool to validate a combine files request and return all errors that might appear. Use when you need to check if files can be combined before executing the actual combine operation.
  - body: { handles: string[], inPlace?: boolean, fileName?: string, folderHandle?: string, addInputFilename?: boolean }
- `POST https://api.mcp.ai/api/gigasheet/validate/files/combine/by/name` — Tool to validate a combine by name request before executing it. Use when you need to check if multiple files can be combined by matching column names, and identify any potential errors or issues.
  - body: { handles: string[], new_sheet_name: string, addInputFilename?: boolean, case_insensitive?: boolean, trim_column_names?: boolean, add_unmatched_columns?: boolean }

## Example prompts
- "What can I do in Gigasheet?"
- "Show me a summary of my Gigasheet account"

## More
- Page: https://mcp.ai/gigasheet
- Agent spec (llms.txt): https://mcp.ai/gigasheet/llms.txt
- Postman collection: https://mcp.ai/gigasheet/postman.json