CircleCI/mcp-server-circleci

CircleCI MCP Server

Model Context Protocol (MCP) is a new, standardized protocol for managing context between large language models (LLMs) and external systems. In this repository, we provide an MCP Server for CircleCI.

This lets you use Cursor IDE, or any MCP Client, to use natural language to accomplish things with CircleCI, e.g.:

Find the latest failed pipeline on my branch and get logs https://github.com/CircleCI-Public/mcp-server-circleci/wiki#circleci-mcp-server-with-cursor-ide

https://github.com/user-attachments/assets/3c765985-8827-442a-a8dc-5069e01edb74

Requirements

pnpm package manager - Learn more
Node.js >= v18.0.0
CircleCI API token - you can generate one through the CircleCI. Learn more or click here for quick access.

Installation

Cursor

Add the following to your cursor MCP config:

{
  "mcpServers": {
    "circleci-mcp-server": {
      "command": "npx",
      "args": ["-y", "@circleci/mcp-server-circleci"],
      "env": {
        "CIRCLECI_TOKEN": "your-circleci-token",
        "CIRCLECI_BASE_URL": "https://circleci.com" // Optional - required for on-prem customers only
      }
    }
  }
}

See the guide below for more information on using MCP servers with cursor: https://docs.cursor.com/context/model-context-protocol#configuring-mcp-servers

VS Code

To install CircleCI MCP Server for VS Code in .vscode/mcp.json

{
  // 💡 Inputs are prompted on first server start, then stored securely by VS Code.
  "inputs": [
    {
      "type": "promptString",
      "id": "circleci-token",
      "description": "CircleCI API Token",
      "password": true
    }
  ],
  "servers": {
    // https://github.com/ppl-ai/modelcontextprotocol/
    "circleci-mcp-server": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@circleci/mcp-server-circleci"],
      "env": {
        "CIRCLECI_TOKEN": "${input:circleci-token}"
      }
    }
  }
}

See the guide below for more information on using MCP servers with VS Code: https://code.visualstudio.com/docs/copilot/chat/mcp-servers

Claude Desktop

Add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "circleci-mcp-server": {
      "command": "npx",
      "args": ["-y", "@circleci/mcp-server-circleci"],
      "env": {
        "CIRCLECI_TOKEN": "your-circleci-token",
        "CIRCLECI_BASE_URL": "https://circleci.com" // Optional - required for on-prem customers only
      }
    }
  }
}

To find/create this file, first open your claude desktop settings. Then click on "Developer" in the left-hand bar of the Settings pane, and then click on "Edit Config"

This will create a configuration file at:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

See the guide below for more information on using MCP servers with Claude Desktop: https://modelcontextprotocol.io/quickstart/user

Claude Code

After installing Claude Code, run the following command:

claude mcp add circleci-mcp-server -e CIRCLECI_TOKEN=your-circleci-token -- npx -y @circleci/mcp-server-circleci

See the guide below for more information on using MCP servers with Claude Code: https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/tutorials#set-up-model-context-protocol-mcp

Windsurf

Add the following to your windsurf mcp_config.json:

{
  "mcpServers": {
    "circleci-mcp-server": {
      "command": "npx",
      "args": ["-y", "@circleci/mcp-server-circleci"],
      "env": {
        "CIRCLECI_TOKEN": "your-circleci-token",
        "CIRCLECI_BASE_URL": "https://circleci.com" // Optional - required for on-prem customers only
      }
    }
  }
}

Installing via Smithery

To install CircleCI MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @CircleCI-Public/mcp-server-circleci --client claude

See the guide below for more information on using MCP servers with windsurf: https://docs.windsurf.com/windsurf/mcp

Features

Supported Tools

get_build_failure_logs

Retrieves detailed failure logs from CircleCI builds. This tool can be used in two ways:
1. Using CircleCI URLs:
  - Provide a failed job URL or pipeline URL directly
  - Example: "Get logs from https://app.circleci.com/pipelines/github/org/repo/123"
2. Using Local Project Context:
  - Works from your local workspace by providing:
    - Workspace root path
    - Git remote URL
    - Branch name
  - Example: "Find the latest failed pipeline on my current branch"
The tool returns formatted logs including:
- Job names
- Step-by-step execution details
- Failure messages and context
This is particularly useful for:
- Debugging failed builds
- Analyzing test failures
- Investigating deployment issues
- Quick access to build logs without leaving your IDE
find_flaky_tests

Identifies flaky tests in your CircleCI project by analyzing test execution history. This leverages the flaky test detection feature described here: https://circleci.com/blog/introducing-test-insights-with-flaky-test-detection/#flaky-test-detection

This tool can be used in two ways:
1. Using CircleCI Project URL:
  - Provide the project URL directly from CircleCI
  - Example: "Find flaky tests in https://app.circleci.com/pipelines/github/org/repo"
2. Using Local Project Context:
  - Works from your local workspace by providing:
    - Workspace root path
    - Git remote URL
  - Example: "Find flaky tests in my current project"
The tool returns detailed information about flaky tests, including:
- Test names and file locations
- Failure messages and contexts
This helps you:
- Identify unreliable tests in your test suite
- Get detailed context about test failures
- Make data-driven decisions about test improvements
get_latest_pipeline_status

Retrieves the status of the latest pipeline for a given branch. This tool can be used in two ways:
1. Using CircleCI Project URL:
  - Provide the project URL directly from CircleCI
  - Example: "Get the status of the latest pipeline for https://app.circleci.com/pipelines/github/org/repo"
2. Using Local Project Context:
  - Works from your local workspace by providing:
    - Workspace root path
    - Git remote URL
    - Branch name
  - Example: "Get the status of the latest pipeline for my current project"
The tool returns a formatted status of the latest pipeline:
- Workflow names and their current status
- Duration of each workflow
- Creation and completion timestamps
- Overall pipeline health
Example output:
```
---
Workflow: build
Status: success
Duration: 5 minutes
Created: 4/20/2025, 10:15:30 AM
Stopped: 4/20/2025, 10:20:45 AM
---
Workflow: test
Status: running
Duration: unknown
Created: 4/20/2025, 10:21:00 AM
Stopped: in progress
```
This is particularly useful for:
- Checking the status of the latest pipeline
- Getting the status of the latest pipeline for a specific branch
- Quickly checking the status of the latest pipeline without leaving your IDE
get_job_test_results

Retrieves test metadata for CircleCI jobs, allowing you to analyze test results without leaving your IDE. This tool can be used in two ways:
1. Using CircleCI URL (Recommended):
  - Provide a CircleCI URL in any of these formats:
    - Job URL: "https://app.circleci.com/pipelines/github/org/repo/123/workflows/abc-def/jobs/789"
    - Workflow URL: "https://app.circleci.com/pipelines/github/org/repo/123/workflows/abc-def"
    - Pipeline URL: "https://app.circleci.com/pipelines/github/org/repo/123"
  - Example: "Get test results for https://app.circleci.com/pipelines/github/org/repo/123/workflows/abc-def"
2. Using Local Project Context:
  - Works from your local workspace by providing:
    - Workspace root path
    - Git remote URL
    - Branch name
  - Example: "Get test results for my current project on the main branch"
The tool returns detailed test result information:
- Summary of all tests (total, successful, failed)
- Detailed information about failed tests including:
  - Test name and class
  - File location
  - Error messages
  - Runtime duration
- List of successful tests with timing information
This is particularly useful for:
- Quickly analyzing test failures without visiting the CircleCI web UI
- Identifying patterns in test failures
- Finding slow tests that might need optimization
- Checking test coverage across your project
- Troubleshooting flaky tests
Note: The tool requires that test metadata is properly configured in your CircleCI config. For more information on setting up test metadata collection, see: https://circleci.com/docs/collect-test-data/
config_helper

Assists with CircleCI configuration tasks by providing guidance and validation. This tool helps you:
1. Validate CircleCI Config:
  - Checks your .circleci/config.yml for syntax and semantic errors
  - Example: "Validate my CircleCI config"
The tool provides:
- Detailed validation results
- Configuration recommendations
This helps you:
- Catch configuration errors before pushing
- Learn CircleCI configuration best practices
- Troubleshoot configuration issues
- Implement CircleCI features correctly
create_prompt_template

Helps generate structured prompt templates for AI-enabled applications based on feature requirements. This tool:
1. Converts Feature Requirements to Structured Prompts:
  - Transforms user requirements into optimized prompt templates
  - Example: "Create a prompt template for generating bedtime stories by age and topic"
The tool provides:
- A structured prompt template
- A context schema defining required input parameters
This helps you:
- Create effective prompts for AI applications
- Standardize input parameters for consistent results
- Build robust AI-powered features
recommend_prompt_template_tests

Generates test cases for prompt templates to ensure they produce expected results. This tool:
1. Provides Test Cases for Prompt Templates:
  - Creates diverse test scenarios based on your prompt template and context schema
  - Example: "Generate tests for my bedtime story prompt template"
The tool provides:
- An array of recommended test cases
- Various parameter combinations to test template robustness
This helps you:
- Validate prompt template functionality
- Ensure consistent AI responses across inputs
- Identify edge cases and potential issues
- Improve overall AI application quality

Development

Getting Started

Clone the repository:

git clone https://github.com/CircleCI-Public/mcp-server-circleci.git
cd mcp-server-circleci

Install dependencies:
```
pnpm install
```
Build the project:
```
pnpm build
```

Development with MCP Inspector

The easiest way to iterate on the MCP Server is using the MCP inspector. You can learn more about the MCP inspector at https://modelcontextprotocol.io/docs/tools/inspector

Start the development server:

pnpm watch # Keep this running in one terminal

In a separate terminal, launch the inspector:
```
pnpm inspector
```
Configure the environment:
- Add your CIRCLECI_TOKEN to the Environment Variables section in the inspector UI
- The token needs read access to your CircleCI projects
- Optionally you can set your CircleCI Base URL. Defaults to https//circleci.com

Testing

Run the test suite:
```
pnpm test
```
Run tests in watch mode during development:
```
pnpm test:watch
```

For more detailed contribution guidelines, see CONTRIBUTING.md