Rag Knowledge Mcp
Hook your coding agent to a stdio RAG knowledge MCP server so it can index and query your docs while you build features.
Overview
rag-knowledge-mcp is an MCP server for the Build phase that lets coding agents run RAG-style knowledge indexing and queries over your corpora.
What is this MCP server?
- stdio MCP server rag-knowledge-mcp v1.0.4 (PyPI) from MEOK AI Labs
- Baseline RAG knowledge tooling sibling to rag-knowledge-graph-mcp
- Designed for agent sessions over Model Context Protocol, not a standalone web app
- Open GitHub repo under CSOAI-ORG for indie self-hosting
- Faster path when graph complexity is not required yet
- Version 1.0.4 with stdio transport
- PyPI identifier: rag-knowledge-mcp
- GitHub: CSOAI-ORG/rag-knowledge-mcp
What problem does it solve?
Agents without RAG force you to manually paste context every session, which does not scale for solo builders with growing docs and codebases.
Who is it for?
First RAG integration for indie agent products, doc assistants, and support bots where chunk search is enough for v1.
Skip if: Use cases demanding rich entity graphs on day one—prefer rag-knowledge-graph-mcp—or teams needing turnkey hosted RAG with SLAs.
What do I get? / Deliverables
After MCP registration, your agent can call knowledge retrieval tools against the pipeline you connect behind this server.
- Agent-accessible RAG knowledge tools via MCP
- Reusable retrieval hook for support and in-repo Q&A workflows
Recommended MCP Servers
Journey fit
How it compares
Streamlined RAG MCP integration, not the graph variant and not an agent SKILL.md workflow.
Common Questions / FAQ
Who is rag-knowledge-mcp for?
Solo builders and small teams wiring Claude Code, Cursor, or Codex to document retrieval without building custom MCP tooling from zero.
When should I use rag-knowledge-mcp?
Use it during Build when standing up agent knowledge access, and in Grow when the same stack powers customer or internal support answers.
How do I add rag-knowledge-mcp to my agent?
Install the PyPI package rag-knowledge-mcp at v1.0.4, configure stdio MCP in your agent, and connect your vector or document store per project docs.