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MCP verified MIT Self-run

Codebase RAG

mcp-bluewings1211-codebase-rag · by bluewings1211

A Retrieval-Augmented Generation (RAG) Model-Controller-Provider (MCP) server designed to assist AI agents and developers in understanding and navigating codebases.. It supports incremental indexing and multi-language parsing, enabling LLMs to understand and interact with code.

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Install

$ agentstack add mcp-bluewings1211-codebase-rag

✓ 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 No
  • ✓ 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.

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About

Codebase RAG MCP Server

A Retrieval-Augmented Generation (RAG) Model-Controller-Provider (MCP) server designed to assist AI agents and developers in understanding and navigating codebases.

Quick Links

  • [Getting Started](GETTING_STARTED.md): Installation and Basic Usage.
  • [User Manual](MANUAL.md): Tutorials, Features, and Advanced Usage.
  • [Configuration](docs/CONFIGURATION.md): Environment variables and performance tuning.
  • [Architecture](ARCHITECTURE.md): System design and high-level overview.
  • [Contributing](CONTRIBUTING.md): Developer setup and guidelines.

Overview

This tool allows you to "chat" with your code. It indexes your local directories or GitHub repositories into a vector database (Qdrant), allowing Large Language Models to perform semantic searches and retrieve accurate code snippets.

Key Features

  • 🔍 Semantic Search: Find code by meaning, not just keywords.
  • 🎯 Two-Stage RAG: 22-31% accuracy improvement with cross-encoder reranking (Qwen3-Reranker).
  • 🧠 Intelligent Chunking: Parses code into functions and classes using Tree-sitter for better context.
  • ⚡ High Performance: Supports incremental indexing and MPS acceleration on macOS.
  • 🌐 Multi-Language: Supports Python, JavaScript, TypeScript, Go, Rust, Java, C++, and more.
  • 📝 File Logging: Optional centralized logging with automatic rotation for debugging.

Quick Start

  1. Setup:

``bash ./setup.sh ``

  1. Index Code:

``bash uv run python manual_indexing.py -d "." -m clear_existing ``

  1. Connect:

Follow the instructions from setup.sh to add the server to your MCP client (e.g., Claude Desktop).

For detailed instructions, please visit [Getting Started](GETTING_STARTED.md).

Documentation

Detailed documentation is available in the docs/ directory:

  • [MCP Tools Reference](docs/MCP_TOOLS.md)
  • [Architecture Deep Dive](docs/ARCHITECTUREDEEPDIVE.md)

License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

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.

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Versions

  • v0.1.0 Imported from the upstream source.

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