# Vectorshift — how to use (mcp.ai)

Connect your Vectorshift account and use 11 tools for developer tools straight from your AI agent. Connect with your own API key. The End-to-End AI Automations Platform for building and deploying AI workflows, pipelines, chatbots, and knowledge bases.

## Option A — via MCP (recommended)
Remote MCP endpoint (HTTP, streamable): `https://api.mcp.ai/p_vectorshift?ms=1787293440000`
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. `vectorshift_create_chatbot`).

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

### Endpoints
- `POST https://api.mcp.ai/api/vectorshift/create/chatbot` — Tool to create a new chatbot. Chatbots are conversational AI interfaces built on pipelines. Use when you need to create a new chatbot with a specific pipeline configuration.
  - body: { name?: string, input?: string, output?: string, deployed: boolean, pipeline: object, description?: string, slack_config?: object, access_config?: object, twilio_config?: object, deployment_options?: object }
- `POST https://api.mcp.ai/api/vectorshift/delete/chatbot` — Tool to delete a chatbot by its ID. Permanently removes the chatbot from the account. Use when you need to remove a chatbot that is no longer needed.
  - body: { id: string }
- `POST https://api.mcp.ai/api/vectorshift/get/chatbot` — Tool to fetch an existing chatbot by its ID or name. Returns chatbot configuration and metadata. Use when you need to retrieve details about a specific chatbot. Either chatbot ID or name must be provi
  - body: { id?: string, name?: string, org_name?: string, username?: string }
- `POST https://api.mcp.ai/api/vectorshift/get/knowledge/base` — Tool to fetch an existing knowledge base by its ID or name. Returns knowledge base configuration and metadata. Use when you need to retrieve details about a specific knowledge base.
  - body: { id?: string, name?: string, org_name?: string, username?: string }
- `POST https://api.mcp.ai/api/vectorshift/get/pipeline` — Tool to fetch an existing pipeline by its ID or name. Returns pipeline configuration and metadata. Use when you need to retrieve a specific pipeline's details, configuration, or metadata.
  - body: { id?: string, name?: string, org_name?: string, username?: string }
- `POST https://api.mcp.ai/api/vectorshift/list/chatbots` — Tool to list all available chatbots in the account. Use when you need to retrieve chatbot IDs or full chatbot details.
  - body: { verbose?: boolean, include_shared?: boolean }
- `POST https://api.mcp.ai/api/vectorshift/list/pipelines` — Tool to list all available pipelines in the VectorShift account. Use when you need to retrieve the catalog of pipelines. Supports filtering for shared pipelines and verbose output with full pipeline d
  - body: { verbose?: boolean, include_shared?: boolean }
- `POST https://api.mcp.ai/api/vectorshift/list/transformations` — Tool to list all available transformations in the account. Use when you need to retrieve transformation IDs or complete transformation objects.
  - body: { verbose?: boolean, include_shared?: boolean }
- `POST https://api.mcp.ai/api/vectorshift/run/pipeline` — Tool to run a VectorShift pipeline with the given inputs. Use when you need to execute a pipeline and get its results or run_id for asynchronous execution. Returns the pipeline execution status, run_i
  - body: { id: string, inputs?: object, conversation_id?: string }
- `POST https://api.mcp.ai/api/vectorshift/run/pipeline/bulk` — Tool to run a VectorShift pipeline in bulk with multiple sets of inputs. Use when you need to batch process multiple pipeline executions in a single API call. Returns the overall status and an array o
  - body: { id: string, runs: object[] }
- `POST https://api.mcp.ai/api/vectorshift/terminate/pipeline` — Tool to terminate a running pipeline execution. Use when you need to stop a pipeline run by its run_id.
  - body: { id: string, run_id: string }

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

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