Claude Context Local

The claude-context-local MCP Server provides intelligent code search that runs entirely on your local machine.

It uses Google’s EmbeddingGemma model to understand the meaning of your code, and allows you to find code by concept, not just keywords. Your code, API keys, and searches never leave your device.

The server integrates directly with Claude Code through the Model Context Protocol, so your workflow remains the same but becomes faster and more private.

Features

• 🔍 Semantic Search: Find code by its functionality and meaning using natural language queries.
• 🔒 Complete Privacy: All processing, from embedding to indexing, occurs 100% locally on your machine.
• 💰 Zero Cost: No API keys or cloud services required; it’s free to run after installation.
• 🗂️ Multi-Language Support: Indexes and searches across 9+ languages, including Python, JavaScript, TypeScript, Go, Java, and Rust.
• ⚡ Intelligent Chunking: Uses AST-based and tree-sitter parsing to break code into logical chunks like functions, classes, and methods.
• 🚀 Performance Optimized: Leverages FAISS for fast similarity search and can utilize GPU acceleration when available.

Use Cases

• Understanding Large Legacy Codebases: Quickly get up to speed on an unfamiliar project. Instead of manually grepping for keywords, you can ask “how is user data serialized?” and the server will find all relevant serialization logic, even if the code doesn’t contain those exact words.
• Refactoring and Code Reuse: Identify duplicate functionality or find existing implementations to avoid rewriting code. A query like “find all functions that validate email addresses” can reveal opportunities to consolidate logic into a shared utility.
• Enhancing Claude Code’s Context: Drastically reduce the context tokens needed when working with Claude on a large codebase. Instead of pasting multiple files, you can rely on the MCP server to pull in precisely the relevant code sections based on semantic understanding.
• Auditing for Security and Compliance: Locate all code segments that handle sensitive operations, such as “find code that accesses the database” or “show me where user permissions are checked,” ensuring a thorough review process.

How To Use It

1. Install the claude-context-local MCP Server:

curl -fsSL https://raw.githubusercontent.com/FarhanAliRaza/claude-context-local/main/scripts/install.sh | bash

If you prefer wget, use this command:

wget -qO- https://raw.githubusercontent.com/FarhanAliRaza/claude-context-local/main/scripts/install.sh | bash

2. Add the server to Claude Code. This allows Claude to communicate with your local search engine.

claude mcp add code-search --scope user -- uv run --directory ~/.local/share/claude-context-local python mcp_server/server.py

3. Open Claude Code and ask it to “index this codebase.” The MCP server will begin chunking and embedding your code. The first index may take some time, but subsequent updates are incremental and much faster.

4. Once indexed, you can interact with it through natural language in the Claude Code chat. No special commands are needed. Just ask questions about your code.

FAQs

Q: What happens if the model fails to download?
A: A download failure is often due to a poor internet connection or insufficient disk space. The google/embeddinggemma-300m model is hosted on Hugging Face, which may require you to accept terms on their website or authenticate your device. You can do this by running uv run huggingface-cli login and pasting an access token.

Q: Will this slow down my machine?
A: The initial indexing process can be resource-intensive, as it involves loading the model, parsing code, and generating embeddings. However, after the first run, searches are very fast, and subsequent indexing is incremental. The system automatically leverages an NVIDIA GPU or Apple Silicon for acceleration if available, but it runs perfectly fine on a CPU.

Q: Do I need to re-index the entire project after every file change?
A: No. The server uses a Merkle-driven incremental indexer. It detects which files have changed and only processes the new or modified code, making updates very efficient.

Q: How is this different from my IDE’s search function?
A: Standard search tools find exact text matches. This server performs semantic search, meaning it understands the intent behind your query. For example, you can search for “a function that validates user credentials,” and it will find relevant code even if the function is named authenticate_user and contains different keywords.