# Feathery — how to use (mcp.ai)

Connect your Feathery account and use 19 tools for forms and surveys straight from your AI agent. Connect with your own API key. Feathery is an AI-powered data intake workflow platform that enables users to build customizable forms with advanced logic and integrations.

## Option A — via MCP (recommended)
Remote MCP endpoint (HTTP, streamable): `https://api.mcp.ai/p_feathery?ms=1787295900000`
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. `feathery_account_edit`).

## Option B — via direct REST API
Base URL: `https://api.mcp.ai/api/feathery`
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/feathery/_endpoints`

### Endpoints
- `POST https://api.mcp.ai/api/feathery/account/edit` — Tool to edit an existing account’s role and permissions. Use when modifying account settings after confirming identity.
  - body: { role?: string, email?: string, account_id?: string, permission_edit_logic?: boolean, permission_edit_theme?: boolean, permission_edit_form_results?: boolean, permission_invite_collaborators?: boolean, permission_edit_collaborator_template?: boolean }
- `POST https://api.mcp.ai/api/feathery/account/get/info` — Tool to get your Feathery team name and list of accounts. Use when you need to fetch your team's account info.
- `POST https://api.mcp.ai/api/feathery/document/fill/template` — Tool to fill or sign a Feathery document template. Use when you need to generate a completed or signed document file after mapping template fields.
  - body: { user_id?: string, document: string, field_values?: object, signer_email?: string }
- `POST https://api.mcp.ai/api/feathery/document/list/envelopes` — Tool to list generated document envelopes by document or user ID. Use when you need to retrieve envelope records for auditing or tracking.
  - body: { id: string, type: string }
- `POST https://api.mcp.ai/api/feathery/form/create/hidden/field` — Creates a new hidden field in the Feathery account. Hidden fields store non-visible data that can be populated via integrations, the API, embed SDK, or URL parameters. Use this to track metadata like 
  - body: { field_id: string }
- `POST https://api.mcp.ai/api/feathery/form/delete` — Permanently delete a form from your Feathery account. This action is irreversible. Use the 'List Forms' action first to get valid form IDs. The form_id corresponds to the 'id' field in the form list r
  - body: { form_id: string, confirm_delete: boolean }
- `POST https://api.mcp.ai/api/feathery/form/get/schema` — Retrieve the complete schema of a Feathery form including all steps, fields, rules, and translations. Use the List Forms action first to find the form_id. Returns detailed structure for understanding 
  - body: { form_id: string }
- `POST https://api.mcp.ai/api/feathery/form/list` — Tool to list all forms in your Feathery account. Use when you need to view or filter available forms.
  - body: { tags?: string[] }
- `POST https://api.mcp.ai/api/feathery/form/list/hidden/fields` — Tool to list all hidden form fields in the account. Use when you need to retrieve hidden field configuration before processing form submissions.
  - body: { limit?: integer, offset?: integer }
- `POST https://api.mcp.ai/api/feathery/log/list/api/connector/errors` — Tool to list recent API connector error logs for a form. Use after confirming the form ID to troubleshoot integration issues.
  - body: { form_id: string, end_time?: string, start_time?: string }
- `POST https://api.mcp.ai/api/feathery/log/list/email/issues` — Tool to list email bounce and complaint events. Use when you need to diagnose delivery issues for sent emails.
  - body: { end_time?: string, event_type?: string, start_time?: string }
- `POST https://api.mcp.ai/api/feathery/log/list/emails` — Tool to list recently sent emails for a form. Use when you need to review email logs after sending form-based emails.
  - body: { form_id: string, end_time?: string, start_time?: string }
- `POST https://api.mcp.ai/api/feathery/log/list/quick/requests` — Tool to list recent Quik integration request logs for a form. Use when you need to review API requests sent to Quik for a specific form.
  - body: { form_id: string, end_time?: string, start_time?: string }
- `POST https://api.mcp.ai/api/feathery/user/create/or/fetch` — Tool to create a new user or fetch an existing one. Use when you need to ensure a user exists and get their SDK key.
  - body: { id: string }
- `POST https://api.mcp.ai/api/feathery/user/delete` — Tool to delete a specific user by ID. Use when you need to remove a user after confirming the user exists.
  - body: { id: string }
- `POST https://api.mcp.ai/api/feathery/user/get/all/data` — Retrieve all stored data fields for a user or all field definitions in your Feathery account. Use this to fetch form field values submitted by users, or to list all available field definitions. Return
  - body: { id?: string }
- `POST https://api.mcp.ai/api/feathery/user/get/session` — Tool to get a user's form session and progress. Use after authenticating and when you need to retrieve session data.
  - body: { user_id: string }
- `POST https://api.mcp.ai/api/feathery/user/list` — Tool to list all users in your Feathery account. Use when you need to retrieve users with optional creation time or field-based filters.
  - body: { created_after?: string, created_before?: string, filter_field_id?: string, filter_field_value?: string }
- `POST https://api.mcp.ai/api/feathery/workspace/generate/login/token` — Generate a login JWT for a Feathery workspace. This is used for white-label integrations where users authenticate through your system and are automatically logged into Feathery. Prerequisites: - Obtai
  - body: { account_id: string, workspace_id: string }

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

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