This project is a Python-based Model Context Protocol (MCP) server for interacting with Apache Pinot. It is built using the FastMCP framework. It is designed to integrate with Claude Desktop to enable real-time analytics and metadata queries on a Pinot cluster.
It allows you to
- List tables, segments, and schema info from Pinot
- Execute read-only SQL queries
- View index/column-level metadata
- Designed to assist business users via Claude integration
- and much more.
See Pinot MCP in action below:
Prompt:
Can you do a histogram plot on the GitHub events against time

Once Claude is running, click the hammer 🛠️ icon and try these prompts:
- Can you help me analyse my data in Pinot? Use the Pinot tool and look at the list of tables to begin with.
- Can you do a histogram plot on the GitHub events against time
uv is a fast Python package installer and resolver, written in Rust. It's designed to be a drop-in replacement for pip with significantly better performance.
curl -LsSf https://astral.sh/uv/install.sh | sh
# Reload your bashrc/zshrc to take effect. Alternatively, restart your terminal
# source ~/.bashrc# Clone the repository
git clone https://github.com/startreedata/mcp-pinot.git
cd mcp-pinot
uv pip install -e . # Install dependencies
# For development dependencies (including testing tools), use:
# uv pip install -e .[dev] The MCP server expects a uvicorn config style .env file in the root directory to configure the Pinot cluster connection. This repo includes a sample .env.example file that assumes a pinot quickstart setup.
mv .env.example .envTo enable OAuth authentication, set the following environment variables in your .env file:
Required variables (when OAUTH_ENABLED=true):
OAUTH_CLIENT_ID: OAuth client IDOAUTH_CLIENT_SECRET: OAuth client secretOAUTH_BASE_URL: Your MCP server base URLOAUTH_AUTHORIZATION_ENDPOINT: OAuth authorization endpoint URLOAUTH_TOKEN_ENDPOINT: OAuth token endpoint URLOAUTH_JWKS_URI: JSON Web Key Set URI for token verificationOAUTH_ISSUER: Token issuer identifier
Optional variables:
OAUTH_AUDIENCE: Expected audience claim for token validationOAUTH_EXTRA_AUTH_PARAMS: Additional authorization parameters as JSON object (e.g.,{"scope": "openid profile"})
Example configuration:
OAUTH_ENABLED=true
OAUTH_CLIENT_ID=client-id
OAUTH_CLIENT_SECRET=client-secret
OAUTH_BASE_URL=http://localhost:8000
OAUTH_AUTHORIZATION_ENDPOINT=https://example.com/oauth/authorize
OAUTH_TOKEN_ENDPOINT=https://example.com/oauth/token
OAUTH_JWKS_URI=https://example.com/.well-known/jwks.json
OAUTH_ISSUER=https://example.com
OAUTH_AUDIENCE=client-id
OAUTH_EXTRA_AUTH_PARAMS={"scope": "openid profile"}uv --directory . run mcp_pinot/server.pyYou should see logs indicating that the server is running.
Start Pinot QuickStart using docker:
docker run --name pinot-quickstart -p 2123:2123 -p 9000:9000 -p 8000:8000 -d apachepinot/pinot:latest QuickStart -type batchQuery MCP Server
uv --directory . run examples/example_client.pyThis quickstart just checks all the tools and queries the airlineStats table.
vi ~/Library/Application\ Support/Claude/claude_desktop_config.json{
"mcpServers": {
"pinot_mcp": {
"command": "/path/to/uv",
"args": [
"--directory",
"/path/to/mcp-pinot-repo",
"run",
"mcp_pinot/server.py"
],
"env": {
// You can also include your .env config here
}
}
}
}Replace /path/to/uv with the absolute path to the uv command, you can run which uv to figure it out.
Replace /path/to/mcp-pinot with the absolute path to the folder where you cloned this repo.
Note: you must use stdio transport when running your server to use with Claude desktop.
You could also configure environment variables here instead of the .env file, in case you want to connect to multiple pinot clusters as MCP servers.
Claude will now auto-launch the MCP server on startup and recognize the new Pinot-based tools.
Apache Pinot MCP server now supports DXT desktop extensions file
To use it, you first need to install dxt via
npm install -g @anthropic-ai/dxt
then you can run the following commands:
uv pip install -r pyproject.toml --target mcp_pinot/lib
uv pip install . --target mcp_pinot/lib
dxt packAfter this you'll get a .dxt file in your dir. Double click on that file to install it in claude desktop
- All tools are defined in the
Pinotclass inutils/pinot_client.py
Build the project with
pip install -e ".[dev]"Test the repo with:
pytestdocker build -t mcp-pinot .docker run -v $(pwd)/.env:/app/.env mcp-pinotNote: Make sure to have your .env file configured with the appropriate Pinot cluster settings before running the container.
