mcp-metricflow 1.0.0

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

mcp-metricflow

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

• mcp-metricflow
  • Table of Contents
  • Overview
  • Setup
  • Configuration
  • Running the MCP Server
    • STDIO Mode ✅
    • SSE Mode 🚧
      • API Key Authentication
  • Available Tools
  • Project Structure
  • Contributing ✨

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=/path/to/.dbt
MF_PATH=mf
MF_TMP_DIR=/path/to/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 --with "mcp-metricflow[snowflake]" mcp-metricflow

Sample .env file:

DBT_PROJECT_DIR=/Users/xxx/sources/jaffle-shop
DBT_PROFILES_DIR=/Users/xxx/.dbt
MF_TMP_DIR=/Users/xxx/.dbt/tmp

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

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

NOTE: Currently only support Snowflake with this extra dependency specified: "--with", "mcp-metricflow[snowflake]"

NOTE: We might have to use absolute path for example: /Users/xxx/.local/bin/uvx instead of uvx alone. Use which uvx to get the full path

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 💌

Finally, super thanks to our Contributors: