MCP server · RAGFlow

RAGFlow MCP Server

A first-party Model Context Protocol server that InfiniFlow ships inside the RAGFlow repository at mcp/server/server.py. It is an OPTIONAL, DISABLED-BY-DEFAULT component of a RAGFlow deployment: the operator uncomments services.ragflow.command in docker/docker-compose.yml (or runs `uv run mcp/server/server.py`) to start it alongside a working RAGFlow server. There is no InfiniFlow-hosted MCP endpoint — cloud.ragflow.io/mcp answers HTTP 405 from openresty, confirming no MCP surface is exposed on RAGFlow Cloud.

View descriptor → RAGFlow provider profile

One-click install for Cursor, VS Code, Claude, and 20+ other MCP clients, powered by API Commons MCP Install — visit install.apicommons.org for more information.

⚠ Proposed MCP surface. No official hosted MCP server was found for RAGFlow. The tools below are a candidate set derived from this provider's API, and the link points at the source descriptor rather than a live server. If RAGFlow publishes an official server, this page will update to it on the next build.

Provider: RAGFlow Type: Candidate descriptor Transport: Host: raw.githubusercontent.com

Descriptor

https://raw.githubusercontent.com/api-evangelist/ragflow/refs/heads/main/mcp/ragflow-mcp.yml

Candidate descriptor · transport

Tools

ragflow_retrieval — Retrieve relevant chunks from the RAGFlow retrieve interface based on a question. dataset_ids may be omitted or empty to search across all available datasets; document_ids narrows to specific documents. The tool description is generated at runtime and embeds the id + description of every dataset the calling key can see.
ragflow_list_datasets — List all accessible datasets (knowledge bases), returning dataset ids, names and descriptions, so a client can discover what to retrieve from.
ragflow_list_chats — List all accessible chat assistants, returning ids, names and descriptions, so a client can discover which assistants are available for conversation.

About MCP

The Model Context Protocol (MCP) is an open protocol Anthropic introduced for connecting LLM-based agents to external tools and data sources. Providers publish MCP servers that expose their API surface as structured, discoverable tools — an MCP-compatible client (Claude Desktop, Cursor, Cline, Continue, etc.) can connect to the server and call its tools without any per-provider integration code.

Browse every MCP server on the APIs.io network or compare with the broader Agent Skill surfaces of the same providers.

Work with this as data

Every MCP server here is available over the APIs.io API and to AI agents over MCP.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for mcp servers

4 MCP tools reach this

find_mcpBrowse and filter every MCP server in the catalog.
apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
resolveTurn a domain, URL or GitHub org into the provider it belongs to.
find_cohortsEvery scored population of providers in the catalog.

All 92 tools →

Call it yourself

curl for this page

This MCP server

curl "https://apis.io/api/v1/mcp/ragflow-mcp-server"

All mcp servers

curl "https://apis.io/api/v1/mcp?limit=25"

Discovery needs no key. Ratings and market analysis are Pro.

Get an API key

Free tier, no form to fill in. Signing in shares your email address with us — we store it to create your key and to recognise you if you sign in with another provider. See our Privacy Policy and Terms.

GitHub Google LinkedIn

A second provider on the same verified email joins the account you already have.