timescaledb-mcp

# TimescaleDB MCP Server A Python-based Model Context Protocol (MCP) server for TimescaleDB that enables AI assistants to interact with your time-series database. ## Features - **Async Database Operations**: Built on `asyncpg` for high-performance async database access - **Connection Pooling**: Efficient connection pool management with configurable pool sizes - **MCP Resources**: Schema introspection via MCP resources for tables and hypertables - **MCP Prompts**: Pre-built prompts for common operations (query time-series, analyze hypertables, explore schema) - **SQL Injection Prevention**: Parameterized queries throughout for security - **Comprehensive Error Handling**: Custom exceptions with clear error messages - **Type Safety**: Full type hints and TypedDict support - **6 MCP Tools**: Execute queries, list/describe tables and hypertables, query time-series data - **Structured Logging**: Comprehensive logging for debugging and monitoring ## Installation ### From PyPI ```bash pip install timescaledb-mcp ``` Or using `uv` (faster): ```bash uv pip install timescaledb-mcp ``` The package is available on [PyPI](https://pypi.org/project/timescaledb-mcp/). ### From Source 1. Clone this repository: ```bash git clone https://github.com/brunoprela/timescaledb-mcp.git cd timescaledb-mcp ``` 2. Install using pip: ```bash pip install -e . ``` Or using `uv`: ```bash uv pip install -e . ``` For development with additional tools: ```bash pip install -e ".[dev]" # or uv pip install -e ".[dev]" ``` ## Configuration Configuration is managed via environment variables with the `TIMESCALEDB_` prefix. ### Required Settings ```env TIMESCALEDB_HOST=localhost TIMESCALEDB_PORT=5432 TIMESCALEDB_DATABASE=your_database TIMESCALEDB_USER=your_user TIMESCALEDB_PASSWORD=your_password ``` ### Optional Settings ```env TIMESCALEDB_MIN_POOL_SIZE=1 # Minimum connection pool size (default: 1) TIMESCALEDB_MAX_POOL_SIZE=10 # Maximum connection pool size (default: 10) TIME…