Opik MCP Server Integration

What does “Opik” MCP Server do?

The Opik MCP (Model Context Protocol) Server is a connector that integrates the Opik platform with various development environments and IDEs, providing AI assistants with seamless access to Opik’s unified interface and capabilities. By implementing the MCP standard, Opik MCP Server enables AI-powered workflows to interact with external data sources and services, such as retrieving prompts, managing projects, accessing traces, and gathering metrics. This streamlines development processes by allowing tasks like prompt management, project navigation, trace exploration, and metrics analysis directly from your IDE or AI client, fostering a more context-aware and efficient development experience.

List of Prompts

No explicit prompt templates are listed in the available repository files or documentation.

List of Resources

No explicit resources are listed in the available repository files or documentation.

List of Tools

No explicit tools are detailed in the available repository files or documentation (such as server.py or similar entry point).

Use Cases of this MCP Server

• IDE Integration: Seamlessly connect the Opik platform with your favorite IDE, allowing AI assistants to access Opik features without leaving your coding environment.
• Unified Prompt Access: Centralize and manage prompt templates, making them accessible for reuse and standardization within team workflows.
• Project Navigation: Quickly access and switch between different Opik projects, improving productivity and workflow organization.
• Trace Exploration: Inspect and analyze execution traces from Opik to debug, optimize, and understand AI-driven workflows.
• Metrics Gathering: Retrieve and analyze project metrics from Opik, supporting performance monitoring and data-driven decision-making.

How to set it up

Windsurf

1. Ensure you have Node.js installed (recommended version 20.11.0 or higher).
2. Locate your Windsurf configuration file.
3. Add the Opik MCP Server to your mcpServers configuration block:

   {
     "mcpServers": {
       "opik-mcp": {
         "command": "npx",
         "args": ["@comet-ml/opik-mcp@latest"]
       }
     }
   }
   

4. Save the configuration file and restart Windsurf.
5. Verify that the Opik MCP Server is running by checking the Windsurf logs or status page.

Securing API Keys (example):

{
  "mcpServers": {
    "opik-mcp": {
      "command": "npx",
      "args": ["@comet-ml/opik-mcp@latest"],
      "env": {
        "OPIK_API_KEY": "${OPIK_API_KEY}"
      },
      "inputs": {
        "apiKey": "${OPIK_API_KEY}"
      }
    }
  }
}

Claude

1. Install Node.js as a prerequisite.
2. Access Claude’s settings/configuration interface.
3. Add the Opik MCP Server with the following configuration:

   {
     "mcpServers": {
       "opik-mcp": {
         "command": "npx",
         "args": ["@comet-ml/opik-mcp@latest"]
       }
     }
   }
   

4. Save and restart Claude.
5. Confirm the Opik MCP Server is connected.

Securing API Keys (example as above).

Cursor

1. Make sure Node.js is installed on your system.
2. Open the Cursor configuration file.
3. Insert the Opik MCP Server entry:

   {
     "mcpServers": {
       "opik-mcp": {
         "command": "npx",
         "args": ["@comet-ml/opik-mcp@latest"]
       }
     }
   }
   

4. Save changes and restart Cursor.
5. Check for successful server registration in the Cursor log/output.

Securing API Keys (example as above).

Cline

1. Install Node.js if not already present.
2. Find Cline’s configuration/settings file.
3. Add the following configuration for Opik MCP Server:

   {
     "mcpServers": {
       "opik-mcp": {
         "command": "npx",
         "args": ["@comet-ml/opik-mcp@latest"]
       }
     }
   }
   

4. Save and restart Cline.
5. Verify the server connection.

Securing API Keys (example as above).

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "opik-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “opik-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the available documentation and repository content, the Opik MCP Server offers a solid integration for IDEs but lacks explicit documentation for prompts, resources, and tools within the repository. The setup process is clear and securing API keys is supported. Given the absence of detailed protocol features, this MCP server is functional for Opik use cases but may need more documentation for advanced MCP capabilities.

MCP Score

Rating:
I would rate this MCP server a 5/10. The implementation is clear and useful for Opik platform integration, but the lack of explicit prompts, resources, or tool documentation prevents it from being a robust, general-purpose MCP server according to the protocol’s full specification.