CircleCI MCP Server Integration

What does “CircleCI” MCP Server do?

The CircleCI MCP Server is a specialized implementation of the Model Context Protocol (MCP) designed to seamlessly integrate with CircleCI’s development workflow. Acting as a bridge between CircleCI’s robust continuous integration infrastructure and the MCP ecosystem, this server empowers AI assistants and tools to access, interact with, and automate tasks within CircleCI environments. By enabling secure and standardized communication between AI models and CircleCI’s APIs, the server facilitates advanced use cases such as automated workflow management, job monitoring, and enhanced build operations. This integration streamlines development pipelines, boosts productivity, and enables intelligent automation and insights across the software delivery lifecycle.

List of Prompts

No information about prompt templates is available in the repository.

List of Resources

No information about specific MCP resources is available in the repository.

List of Tools

No information about tools provided in server.py or equivalent files is available in the repository.

Use Cases of this MCP Server

• AI-powered build monitoring: Enable AI assistants to query the status of builds and jobs within CircleCI, offering real-time feedback and proactive notifications for developers.
• Automated workflow management: Allow AI agents to trigger, configure, or modify CircleCI workflows, making CI/CD pipelines more adaptive and responsive to project changes.
• Insightful analytics and reporting: Provide developers with detailed analytics on build performance, failure trends, and resource utilization by leveraging CircleCI’s data via the MCP server.
• Context-aware troubleshooting: Facilitate the retrieval of logs, artifacts, and error reports so that AI assistants can assist in diagnosing and resolving build issues quickly.
• Seamless integration with development tools: Bridge CircleCI with AI-driven IDE plugins or bots, enabling smoother automation and collaboration within development environments.

How to set it up

Windsurf

1. Ensure Node.js and npm are installed on your system.
2. Locate the Windsurf configuration directory.
3. Add the CircleCI MCP Server to the mcpServers configuration as shown below.
4. Save the configuration and restart Windsurf.
5. Verify connectivity to the server.

{
  "mcpServers": {
    "circleci-mcp": {
      "command": "npx",
      "args": ["@circleci/mcp-server-circleci@latest"]
    }
  }
}

Claude

1. Confirm Node.js is available in your environment.
2. Access Claude’s configuration files.
3. Insert the CircleCI MCP Server configuration in the mcpServers section.
4. Save changes and restart Claude.
5. Check the MCP server status in Claude’s interface.

{
  "mcpServers": {
    "circleci-mcp": {
      "command": "npx",
      "args": ["@circleci/mcp-server-circleci@latest"]
    }
  }
}

Cursor

1. Install Node.js if it’s not present.
2. Open Cursor’s settings or MCP configuration panel.
3. Add an entry for the CircleCI MCP Server.
4. Restart the Cursor application.
5. Confirm that the server is listed and connected.

{
  "mcpServers": {
    "circleci-mcp": {
      "command": "npx",
      "args": ["@circleci/mcp-server-circleci@latest"]
    }
  }
}

Cline

1. Make sure Node.js is installed.
2. Edit the mcpServers configuration file within Cline.
3. Add the CircleCI MCP Server configuration block.
4. Save and restart Cline.
5. Validate the MCP server connection.

{
  "mcpServers": {
    "circleci-mcp": {
      "command": "npx",
      "args": ["@circleci/mcp-server-circleci@latest"]
    }
  }
}

Securing API Keys:
To ensure the security of API keys, use environment variables in your configuration. Example:

{
  "mcpServers": {
    "circleci-mcp": {
      "command": "npx",
      "args": ["@circleci/mcp-server-circleci@latest"],
      "env": {
        "CIRCLECI_TOKEN": "${CIRCLECI_TOKEN_ENV_VAR}"
      },
      "inputs": {
        "apiKey": "${CIRCLECI_TOKEN_ENV_VAR}"
      }
    }
  }
}

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:

{
  "circleci-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 “circleci-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, CircleCI MCP Server offers a clear overview and setup guidance, but lacks publicly documented prompts, resources, and tool primitives in the accessible files. This limits its immediate out-of-the-box discoverability for advanced MCP features.

Our opinion

Given the presence of a clear license, community activity (stars/forks), and robust setup info but missing documentation for resources, prompts, and tools, we would rate this MCP a 4/10 for completeness and developer friendliness at the current stage.

MCP Score