MCP server for chDB — the in-process SQL OLAP engine powered by ClickHouse. Lets AI agents query Parquet, CSV, JSON, and pandas DataFrames with one tool.
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# chdb-mcp [](https://pypi.org/project/chdb-mcp/) [](https://github.com/chdb-io/chdb-mcp/actions/workflows/ci.yml) [](LICENSE) [](https://pypi.org/project/chdb-mcp/) An [MCP](https://modelcontextprotocol.io) server for [chDB](https://chdb.io), the in-process SQL OLAP engine powered by ClickHouse. Lets agents (Claude Desktop, Cursor, VS Code, Codex CLI, Cline, …) query Parquet, CSV, JSON, and pandas DataFrames with one tool — no separate server, no Docker. ## Why chdb-mcp? - **Full ClickHouse engine, in-process.** 1000+ functions (`windowFunnel`, `quantilesTDigest`, `geoToH3`, the `-If`/`-State`/`-Merge` combinators), typed `JSON` with O(1) sub-column reads, native vectors, `MergeTree` storage. - **Drop-in pandas API.** `import datastore as pd` covers ~300 pandas-shaped methods compiled to ClickHouse SQL. v1.0 adds `dataframe_query()` for zero-copy `Python(df)`. - **~80 formats and 12+ source connectors in core.** Parquet, CSV, JSON, Avro, ORC, Arrow, Protobuf, plus `s3()`, `mongodb()`, `postgresql()`, `mysql()`, `iceberg()`, `deltaLake()` — no `INSTALL/LOAD` chain. - **Federate to remote ClickHouse in one statement.** (v0.5) `remoteSecure('cluster:9440', 'db.table', ...)` joins local Parquet with a production ClickHouse cluster in one optimised plan. - **Same SQL as your warehouse.** Copy-paste ClickHouse production queries into the agent prompt — no dialect bridge. ## Install ```bash pip install chdb-mcp ``` ## Connect **Claude Desktop** — add to `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) or `%APPDATA%\Claude\claude_desktop_config.json` (Windows): ```json { "mcpServers": { "chdb": { "command": "chdb-mcp" } } } ``` **Cursor / VS Code** — same JSON in `~/.cursor/mcp.json`…
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