
opik-mcp
Model Context Protocol (MCP) implementation for Opik enabling seamless IDE integration and unified access to prompts, projects, traces, and metrics.
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(Model Context Protocol)
A Model Context Protocol (MCP) implementation for the Opik platform with support for multiple transport mechanisms, enabling seamless integration with IDEs and providing a unified interface for Opik's capabilities.
Website • Slack community • Twitter • Documentation
⚠️ Notice: SSE (Server-Sent Events) transport support is currently experimental and untested. For production use, we recommend using the direct process execution approach shown in the IDE integration examples.
🚀 What is Opik MCP Server?
Opik MCP Server is an open-source implementation of the Model Context Protocol for the Opik platform. It provides a unified interface for interacting with Opik's capabilities, supporting multiple transport mechanisms for flexible integration into various environments.
You can use Opik MCP Server for:
-
IDE Integration:
- Seamlessly integrate with Cursor and other compatible IDEs
- Provide direct access to Opik's capabilities from your development environment
-
Unified API Access:
- Access all Opik features through a standardized protocol
- Leverage multiple transport options (stdio, SSE) for different integration scenarios
-
Platform Management:
- Manage prompts, projects, traces, and metrics through a consistent interface
- Organize and monitor your LLM applications efficiently
Features
- Prompts Management: Create, list, update, and delete prompts
- Projects/Workspaces Management: Organize and manage projects
- Traces: Track and analyze trace data
- Metrics: Gather and query metrics data
Quick Start
Installation
Manual Installation
# Clone the repository
git clone https://github.com/comet-ml/opik-mcp.git
cd opik-mcp
# Install dependencies and build
npm install
npm run build
Configuration
Create a .env
file based on the example:
cp .env.example .env
# Edit .env with your specific configuration
Starting the Server
# Start with stdio transport (default)
npm run start:stdio
# Start with SSE transport for network access (experimental)
npm run start:sse
IDE Integration
Cursor Integration
To integrate with Cursor IDE, create a .cursor/mcp.json
file in your project directory with the following configuration:
{
"mcpServers": {
"opik": {
"command": "/path/to/node",
"args": [
"/path/to/opik-mcp/build/index.js",
"--apiUrl",
"https://www.comet.com/opik/api",
"--apiKey",
"YOUR_API_KEY",
"--workspace",
"default",
"--debug",
"true"
],
"env": {
"OPIK_API_BASE_URL": "https://www.comet.com/opik/api",
"OPIK_API_KEY": "YOUR_API_KEY",
"OPIK_WORKSPACE_NAME": "default",
}
}
}
}
Replace /path/to/node
with the path to your Node.js executable and /path/to/opik-mcp
with the path to your opik-mcp installation. Also replace YOUR_API_KEY
with your actual Opik API key.
Available Commands
The project includes a Makefile for common operations:
# Display all available commands
make help
# Run tests
make test
# Run transport-specific tests
make test-transport
# Start the server with SSE transport (experimental)
make start-sse
# Start the server with stdio transport
make start-stdio
Transport Options
Standard Input/Output
Ideal for local integration where the client and server run on the same machine.
make start-stdio
Server-Sent Events (SSE)
Enables remote access and multiple simultaneous clients over HTTP. Note that this transport option is experimental.
make start-sse
For detailed information about the SSE transport, see docs/sse-transport.md.
Development
Testing
# Run all tests
npm test
# Run specific test suite
npm test -- tests/transports/sse-transport.test.ts
Pre-commit Hooks
This project uses pre-commit hooks to ensure code quality:
# Run pre-commit checks manually
make precommit
Documentation
- SSE Transport - Details on using the SSE transport
- API Reference - Complete API documentation
- Configuration - Advanced configuration options
- IDE Integration - Integration with Cursor IDE
License
Apache 2.0
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Reviews

user_pK7lLev4
I've been using opik-mcp by comet-ml for several months and it's an absolute game changer. Its seamless integration and robust features make machine learning project management so much easier. The detailed documentation and active community support further enhance its utility. Highly recommended for anyone looking to streamline their ML workflows!