# Mintlify — how to use (mcp.ai)

Connect your Mintlify account and use 14 tools for developer tools straight from your AI agent. Connect with your own API key. Mintlify is a documentation platform. This toolkit exposes the Admin API for managing docs programmatically, trigger deployments and previews, run automations, drive the docs-editing agent, and export analytics (feedback, searches, views, visitors and assistant conversations).

## Option A — via MCP (recommended)
Remote MCP endpoint (HTTP, streamable): `https://api.mcp.ai/p_mintlify?ms=1787295780000`
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. `mintlify_create_agent_job`).

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

### Endpoints
- `POST https://api.mcp.ai/api/mintlify/create/agent/job` — Start a background documentation agent job from a natural-language prompt. The agent edits the connected docs repo and OPENS A PULL REQUEST if it changes files (DESTRUCTIVE; consumes credits). Returns
  - body: { prompt: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/get/agent/job` — Retrieve the status and details (status, PR link, model, source repo/ref) of a docs agent job. Poll this until status is completed, archived or failed. No pagination.
  - body: { job_id: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/get/assistant/caller/stats` — Get assistant query counts broken down by caller type (web, api, other, total) for a date range. Returns a single aggregate object; no pagination.
  - body: { date_to?: string, date_from?: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/get/assistant/conversations` — Export the AI assistant conversation history (question, answer, cited sources, resolution status) for a Mintlify project, optionally filtered by date. Returns one page of conversations plus a cursor t
  - body: { limit?: integer, cursor?: string, date_to?: string, date_from?: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/get/feedback` — Export a project's user feedback (thumbs / contextual comments / agent feedback), optionally filtered by date, source and status. Returns one page plus a cursor to fetch the next.
  - body: { limit?: integer, cursor?: string, source?: string, status?: string, date_to?: string, date_from?: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/get/feedback/by/page` — Get feedback counts (thumbs up/down, code, total) aggregated per documentation page path for a date range. Single page of results — this endpoint exposes no pagination cursor, so only the first page i
  - body: { limit?: integer, source?: string, status?: string, date_to?: string, date_from?: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/get/page/views` — Export per-path and site-wide content view counts split by human vs AI traffic. Offset-paginated: returns one page of rows plus site-wide totals, the hasMore flag as has_more, and a next_offset to fet
  - body: { limit?: integer, offset?: integer, date_to?: string, date_from?: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/get/search/queries` — Export documentation search terms ordered by hit count (with CTR and top clicked page). Returns one page plus a cursor to fetch the next; there is no more-flag, so stop paging once next_cursor is null
  - body: { limit?: integer, cursor?: string, date_to?: string, date_from?: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/get/unique/visitors` — Export per-path and site-wide approximate distinct visitor counts split by human vs AI traffic. Offset-paginated: returns one page plus a `has_more` flag and the effective `next_offset` to fetch the f
  - body: { limit?: integer, offset?: integer, date_to?: string, date_from?: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/get/update/status` — Get the status and details (queued / in_progress / success / failure, logs, commit, screenshot) of a triggered deployment update by its statusId. Poll this with the statusId returned by MINTLIFY_TRIGG
  - body: { status_id: string }
- `POST https://api.mcp.ai/api/mintlify/send/agent/message` — Send a follow-up instruction to an existing, in-progress docs agent job (asynchronous). Use to refine or continue work on a job created by create_agent_job. Returns the updated AgentJob; poll get_agen
  - body: { job_id: string, prompt: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/trigger/automation` — Trigger a custom-schedule automation (workflow) to run immediately. Returns the schemaId, instanceId and jobId of the launched run. Only custom-schedule automations are triggerable (others return 400)
  - body: { project_id: string, workflow_schema_id: string }
- `POST https://api.mcp.ai/api/mintlify/trigger/preview` — Create or update a preview deployment of the docs project for a Git branch (redeploys if a preview already exists for that branch). Returns a statusId to poll with MINTLIFY_GET_UPDATE_STATUS and a pre
  - body: { branch: string, project_id: string }
- `POST https://api.mcp.ai/api/mintlify/trigger/update` — Queue a production deployment of the docs project from its configured branch. Returns a statusId to poll with MINTLIFY_GET_UPDATE_STATUS. Requires a Mintlify plan that includes deployments (otherwise 
  - body: { project_id: string }

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

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