Skip to main content

A Model Context Protocol (MCP) server that provides MetricFlow CLI tools

Project description

mcp-metricflow

Python License Coverage Code style: ruff Package manager: uv

A Model Context Protocol (MCP) server that provides MetricFlow CLI tools through both SSE (with optional API key authentication) and STDIO interfaces.

[!WARNING] This repository is a learning project focused on MetricFlow integration with MCP. For production use cases, please refer to the official dbt-mcp implementation by dbt Labs.

Table of Contents

Overview

This project provides a Model Context Protocol (MCP) server that wraps MetricFlow CLI commands, making them accessible through both Server-Sent Events (SSE) and Standard Input/Output (STDIO) interfaces. It enables seamless integration with Claude Desktop and other MCP-compatible clients.

Setup

# Install uv at https://docs.astral.sh/uv/getting-started/installation/

# Copy environment template
cp .env.template .env
# ...and then jump to # Configuration section to fulfill it

Configuration

Edit the .env file with your specific configuration:

# Required: Path to your dbt project
DBT_PROJECT_DIR=/path/to/your/dbt/project e.g. /Users/dat/repos/il/jaffle-shop

# Optional: Other configurations
DBT_PROFILES_DIR=~/.dbt
MF_PATH=mf
MF_TMP_DIR=/tmp

# SSE server configuration (optional)
MCP_HOST=localhost
MCP_PORT=8000

# API key authentication for SSE mode (optional)
MCP_API_KEY=your-secret-api-key
MCP_REQUIRE_AUTH=false

Running the MCP Server

STDIO Mode

For integration with Claude Desktop (or any other MCP Client tool), use STDIO mode with the following uvx command:

uvx --env-file /path/to/.env mcp-metricflow

Add this configuration to the respective client's config file:

{
  "mcpServers": {
    "dbt-mcp": {
      "command": "uvx",
      "args": [
        "--env-file",
        "<path-to-.env-file>",
        "mcp-metricflow"
      ]
    },
  }
}

SSE Mode

For web-based integration or direct HTTP access:

# export DBT_PROFILES_DIR=~/.dbt
uv run python src/main_sse.py

The server will start on http://localhost:8000 (or the host/port specified in your environment variables).

API Key Authentication

The SSE server supports optional API key authentication. To enable authentication:

  1. Set the required environment variables:

    export MCP_API_KEY="your-secret-api-key"
    export MCP_REQUIRE_AUTH="true"
    
  2. Access authenticated endpoints by including the API key in the Authorization header:

    # Health check (no authentication required)
    curl http://localhost:8000/health
    
    # SSE endpoint (requires authentication when enabled)
    curl -H "Authorization: Bearer your-secret-api-key" http://localhost:8000/sse
    

Authentication Configuration:

  • MCP_API_KEY: The secret API key for authentication (required when MCP_REQUIRE_AUTH=true)
  • MCP_REQUIRE_AUTH: Enable/disable authentication (true, 1, yes, on to enable; default: false)

Security Notes:

  • The /health endpoint is always accessible without authentication for monitoring purposes
  • The /sse endpoint requires authentication when MCP_REQUIRE_AUTH=true
  • API keys are case-sensitive and support special characters
  • Store API keys securely and avoid committing them to version control

Available Tools

The MCP server exposes the following MetricFlow CLI tools:

Tool Description Required Parameters Optional Parameters
query Execute MetricFlow queries session_id, metrics group_by, start_time, end_time, where, order, limit, saved_query, explain, show_dataflow_plan, show_sql_descriptions
list_metrics List available metrics None search, show_all_dimensions
list_dimensions List available dimensions None metrics
list_entities List available entities None metrics
list_dimension_values List values for a dimension dimension, metrics start_time, end_time
validate_configs Validate model configurations None dw_timeout, skip_dw, show_all, verbose_issues, semantic_validation_workers
health_checks Perform system health checks None None

Each tool includes comprehensive documentation accessible through the MCP interface.

Project Structure

src/
├── config/
│   └── config.py              # Configuration management
├── server/
│   ├── auth.py                # API key authentication
│   ├── sse_server.py          # SSE server implementation
│   └── stdio_server.py        # STDIO server implementation
├── tools/
│   ├── prompts/mf_cli/        # Tool documentation (*.md files)
│   ├── metricflow/            # MetricFlow CLI wrappers
│   │   ├── base.py            # Shared command execution
│   │   ├── query.py           # Query functionality
│   │   ├── list_metrics.py    # List metrics
│   │   ├── list_dimensions.py # List dimensions
│   │   ├── list_entities.py   # List entities
│   │   ├── list_dimension_values.py # List dimension values
│   │   ├── validate_configs.py # Configuration validation
│   │   └── health_checks.py   # Health checks
│   └── cli_tools.py           # MCP tool registration
├── utils/
│   ├── logger.py              # Logging configuration
│   └── prompts.py             # Prompt loading utilities
├── main_sse.py                # SSE server entry point
└── main_stdio.py              # STDIO server entry point

Contributing ✨

If you've ever wanted to contribute to this tool, and a great cause, now is your chance!

See the contributing docs CONTRIBUTING for more information.

If you've found this tool to be very helpful, please consider giving the repository a star, sharing it on social media, or even writing a blog post about it 💌

mcp-metricflow stars buy me a coffee

Finally, super thanks to our Contributors:

TODO

  • Test STDIO mode

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mcp_metricflow-1.0.0b4.tar.gz (38.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mcp_metricflow-1.0.0b4-py3-none-any.whl (27.4 kB view details)

Uploaded Python 3

File details

Details for the file mcp_metricflow-1.0.0b4.tar.gz.

File metadata

  • Download URL: mcp_metricflow-1.0.0b4.tar.gz
  • Upload date:
  • Size: 38.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for mcp_metricflow-1.0.0b4.tar.gz
Algorithm Hash digest
SHA256 957117a1e2c68613e70d74322221111e023cdad175aaac3118de1d927a3f6d47
MD5 192862f46b3dda460d2583088fd3f561
BLAKE2b-256 12d829cfd89e798d4edec547d8ae639fc6f6270acca12ee2e192fc9c92e753b8

See more details on using hashes here.

Provenance

The following attestation bundles were made for mcp_metricflow-1.0.0b4.tar.gz:

Publisher: pypi-publish.yml on datnguye/mcp-metricflow

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file mcp_metricflow-1.0.0b4-py3-none-any.whl.

File metadata

File hashes

Hashes for mcp_metricflow-1.0.0b4-py3-none-any.whl
Algorithm Hash digest
SHA256 9268cbc0522ebcfa784471f8c036e404a90a0410ed49076c20e5b970bd572ed0
MD5 cddb58e376913ecc265007d71b441c87
BLAKE2b-256 bb9fe2b48ee1d0abf11327d28c5efdb8b06463487e6ae40f4f4f570c7de5ce4d

See more details on using hashes here.

Provenance

The following attestation bundles were made for mcp_metricflow-1.0.0b4-py3-none-any.whl:

Publisher: pypi-publish.yml on datnguye/mcp-metricflow

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page