What is Files Db Mcp

Files-DB-MCP is a local vector database system designed to provide fast and efficient search capabilities for software projects using the Message Control Protocol (MCP). It is particularly useful for LLM coding agents.

Use cases

Use cases include enhancing code navigation in IDEs, providing context-aware code suggestions, facilitating code reviews, and improving code quality through efficient search capabilities.

How to use

To use files-db-mcp, install it by cloning the repository or using the automated installation script. After installation, run ‘files-db-mcp’ in your project directory to start indexing files and respond to MCP search queries.

Key features

Key features include zero configuration setup, real-time monitoring of file changes, semantic vector search for relevant code, compatibility with Claude Code and other LLM tools, and the use of open-source models from Hugging Face for code embeddings.

Where to use

Files-DB-MCP can be used in software development environments, particularly where code search and retrieval are essential, such as in large codebases, collaborative projects, and AI-assisted coding.

Files-DB-MCP: Vector Search for Code Projects

A local vector database system that provides LLM coding agents with fast, efficient search capabilities for software projects via the Message Control Protocol (MCP).

Features

• Zero Configuration - Auto-detects project structure with sensible defaults
• Real-Time Monitoring - Continuously watches for file changes
• Vector Search - Semantic search for finding relevant code
• MCP Interface - Compatible with Claude Code and other LLM tools
• Open Source Models - Uses Hugging Face models for code embeddings

Installation

Option 1: Clone and Setup (Recommended)

# Using SSH (recommended if you have SSH keys set up with GitHub)
git clone [email protected]:randomm/files-db-mcp.git ~/.files-db-mcp && bash ~/.files-db-mcp/install/setup.sh

# Using HTTPS (if you don't have SSH keys set up)
git clone https://github.com/randomm/files-db-mcp.git ~/.files-db-mcp && bash ~/.files-db-mcp/install/setup.sh

Option 2: Automated Installation Script

curl -fsSL https://raw.githubusercontent.com/randomm/files-db-mcp/main/install/install.sh | bash

Usage

After installation, run in any project directory:

files-db-mcp

The service will:

1. Detect your project files
2. Start indexing in the background
3. Begin responding to MCP search queries immediately

Requirements

• Docker
• Docker Compose

Configuration

Files-DB-MCP works without configuration, but you can customize it with environment variables:

• EMBEDDING_MODEL - Change the embedding model (default: ‘jinaai/jina-embeddings-v2-base-code’ or project-specific model)
• FAST_STARTUP - Set to ‘true’ to use a smaller model for faster startup (default: ‘false’)
• QUANTIZATION - Enable/disable quantization (default: ‘true’)
• BINARY_EMBEDDINGS - Enable/disable binary embeddings (default: ‘false’)
• IGNORE_PATTERNS - Comma-separated list of files/dirs to ignore

First-Time Startup

On first run, Files-DB-MCP will download embedding models which may take several minutes depending on:

• The size of the selected model (300-500MB for high-quality models)
• Your internet connection speed

Subsequent startups will be much faster as models are cached in a persistent Docker volume. For faster initial startup, you can:

# Use a smaller, faster model (90MB)
EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 files-db-mcp

# Or enable fast startup mode
FAST_STARTUP=true files-db-mcp

Model Caching

Files-DB-MCP automatically persists downloaded embedding models, so you only need to download them once:

• Models are stored in a Docker volume called model_cache
• This volume persists between container restarts and across different projects
• The cache is shared for all projects using Files-DB-MCP on your machine
• You don’t need to download the model again for each project

Claude Code Integration

Add to your Claude Code configuration:

{
  "mcpServers": {
    "files-db-mcp": {
      "command": "python",
      "args": [
        "/path/to/src/claude_mcp_server.py",
        "--host",
        "localhost",
        "--port",
        "6333"
      ]
    }
  }
}

For details, see Claude MCP Integration.

Documentation

• Installation Guide - Detailed setup instructions
• API Reference - Complete API documentation
• Configuration Guide - Configuration options

Repository Structure

• /src - Source code
• /tests - Unit and integration tests
• /docs - Documentation
• /scripts - Utility scripts
• /install - Installation scripts
• /.docker - Docker configuration
• /config - Configuration files
• /ai-assist - AI assistance files

License

MIT License

Contributing

Contributions welcome! Please feel free to submit a pull request.