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MCP verified MIT Self-run

Rag Code Mcp

mcp-doitmagic-rag-code-mcp · by doITmagic

Privacy-first semantic code navigation MCP server using RAG. Features deep AST multi-language support (Go, PHP/Laravel/WP, JS/TS/React, Python), 100% local LLMs (Ollama), and vector search (Qdrant) for AI IDEs like Cursor, Windsurf, Copilot, and Claude.

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Install

$ agentstack add mcp-doitmagic-rag-code-mcp

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ● Network access Used
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Verified badge

Passed review? Show it. Paste this badge into your README, it links to the public security report.

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Reliability & compatibility

✓ Security review passed
0 installs to date
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○ 5mo ago

Declared compatibility

Claude CodeClaude DesktopCursorWindsurf

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

RagCode MCP - Make Your Codebase AI-Ready

> The privacy-first MCP server that transforms any repository into an AI-ready codebase with semantic search and RAG.

RagCode is a Model Context Protocol (MCP) server that instantly makes your project AI-ready. It enables AI assistants like GitHub Copilot, Cursor, Windsurf, and Claude to understand your entire codebase through semantic vector search, bridging the gap between your code and Large Language Models (LLMs).

Built with the official Model Context Protocol Go SDK, RagCode provides 9 powerful tools to index, search, and analyze code, making it the ultimate solution for AI-ready software development.

⚡ One-Command Installation

No Go, no build tools, no configuration needed. Just Docker.

Linux (amd64)

curl -fsSL https://github.com/doITmagic/rag-code-mcp/releases/latest/download/rag-code-mcp_linux_amd64.tar.gz | tar xz && ./ragcode-installer -ollama=docker -qdrant=docker

macOS (Apple Silicon / Intel)

# Apple Silicon (M1/M2/M3)
curl -fsSL https://github.com/doITmagic/rag-code-mcp/releases/latest/download/rag-code-mcp_darwin_arm64.tar.gz | tar xz && ./ragcode-installer -ollama=docker -qdrant=docker

# Intel Macs
curl -fsSL https://github.com/doITmagic/rag-code-mcp/releases/latest/download/rag-code-mcp_darwin_amd64.tar.gz | tar xz && ./ragcode-installer -ollama=docker -qdrant=docker

Windows (PowerShell)

Invoke-WebRequest -Uri "https://github.com/doITmagic/rag-code-mcp/releases/latest/download/rag-code-mcp_windows_amd64.zip" -OutFile "ragcode.zip"; Expand-Archive ragcode.zip -DestinationPath . -Force; .\ragcode-installer.exe -ollama=docker -qdrant=docker

That's it! The installer automatically:

  • ✅ Downloads and installs the rag-code-mcp binary
  • ✅ Sets up Ollama and Qdrant in Docker containers
  • ✅ Downloads required AI models (phi3:medium, mxbai-embed-large)
  • ✅ Configures your IDE (VS Code, Cursor, Windsurf, Claude Desktop)
  • ✅ Adds binaries to your PATH

🔄 Keep Updated

The auto-update feature is available starting with v1.1.18.

How to Upgrade:

  1. **If you are on an older version (

Built with ❤️ for developers who want smarter AI code assistants

⭐ Star us on GitHub if RagCode helps your workflow!

Questions? Open an Issue • [Read the Docs](./QUICKSTART.md) • Join Discussions

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.

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