Local full-text + vector search with retrieval-first philosophy
Project description
MeshDB
Local full-text + vector search with retrieval-first philosophy.
Installation
pip install meshdb-go
Quick Start
# Check status
meshdb status
# Index your files
meshdb index ~/Documents
# Search
meshdb search "meeting notes"
# Semantic search (requires Ollama)
meshdb semantic "how does authentication work"
Features
- Full-text search (FTS5) with multilingual support
- Semantic search using Ollama embeddings (bge-m3)
- Hybrid search combining keyword + vector similarity
- MCP integration for Claude Desktop
- 100% local - no data leaves your machine
- Sensitive data blocking at indexing time
Requirements
- macOS or Linux
- Python 3.9+
- Ollama (optional, for semantic search)
Ollama Setup (Optional)
For semantic search capabilities:
# Install Ollama
brew install ollama # macOS
# or: curl -fsSL https://ollama.com/install.sh | sh # Linux
# Start Ollama
ollama serve
# Pull embedding model
ollama pull bge-m3
Claude Desktop Integration
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"meshdb": {
"command": "meshdb",
"args": ["mcp"]
}
}
}
Documentation
License
MIT
Project details
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