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Files-DB-MCP

by randomm

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

# Using SSH (recommended if you have SSH keys set up with GitHub) git clone git@github.com: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

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.

-
security - not tested
A
license - permissive license
-
quality - not tested

local-only server

The server can only run on the client's local machine because it depends on local resources.

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

  1. Features
    1. Installation
      1. Option 1: Clone and Setup (Recommended)
      2. Option 2: Automated Installation Script
    2. Usage
      1. Requirements
        1. Configuration
          1. First-Time Startup
          2. Model Caching
        2. Claude Code Integration
          1. Documentation
            1. Repository Structure
              1. License
                1. Contributing

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