RAGFlow
RAGFlow is the open-source Retrieval-Augmented Generation engine built by InfiniFlow Inc. It combines deep document understanding (DeepDoc parsing of PDFs, images, tables and scanned files) with hybrid retrieval — dense vector search, BM25 full-text and tensor/multi-vector re-ranking — and an integrated visual agent platform, to serve as a context layer for LLM applications. The platform ships as an Apache-2.0 self-hosted Docker deployment and as RAGFlow Cloud, a hosted multi-tenant service. Its RESTful HTTP API covers dataset (knowledge base) management, document ingestion and parsing, chunk management, retrieval, chat assistants, sessions, agents, memory, workspace file versioning and search apps, plus an OpenAI-compatible chat-completions surface. A first-party Python SDK and an optional self-hosted Model Context Protocol server expose the same retrieval core to agents.
RAGFlow publishes 1 API on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Retrieval Augmented Generation, Search, and Vector Database.
RAGFlow’s developer surface includes documentation, getting-started guide, API reference, engineering blog, support, pricing, signup flow, and 30 more developer resources.
APIs 1
Individual APIs this provider publishes, each with its own machine-readable definition.
RAGFlow HTTP API
The RAGFlow RESTful HTTP API — 95 documented operations under /api/v1, authenticated with a tenant API key carried as a bearer token. Covers dataset management, document upload ...
MCP Servers 1
Model Context Protocol servers that expose these APIs to AI agents.
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 RA...
MCP SERVERPricing Plans 1
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Rate Limits 1
Documented rate limits and quota policies.
Ragflow Rate Limits
RATE LIMITSSecurity Posture 3
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Get Started 3
Portal, sign-up, and the first successful call
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 3
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 6
Pagination, idempotency, versioning, errors, and events
Build 5
SDKs, sample code, and the tooling you integrate with
Access & Security 5
Authentication, authorization, and security posture
Operate 7
Status, limits, changes, and where to get help
Scroll for all 7
Commercial 4
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
Source (apis.yml)
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MCP server
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