What is CircleCI MCP Server?

The CircleCI MCP Server is an implementation of the Model Context Protocol (MCP) for CircleCI, allowing AI agents to interact with CircleCI's API to manage build failures and automate CI/CD tasks directly from development environments like VS Code, Cursor IDE, and others.

How to use CircleCI MCP Server?

Installation:
- Choose between NPX or Docker installation methods.
- Configure the server in your preferred environment (VS Code, Cursor, Claude Desktop, etc.) by adding the server configuration to the respective config files.
- Provide a CircleCI Personal API Token for authentication.
Usage:
- Use natural language commands to interact with CircleCI tasks:
  - Example: "Find the latest failed pipeline on my branch and get logs"
- The server supports various tools for retrieving logs, analyzing test results, managing pipelines, and more.

Key features of CircleCI MCP Server

Build Failure Logs: Retrieve detailed failure logs from CircleCI builds.
Flaky Test Detection: Identify unreliable tests in your test suite.
Pipeline Status: Check the status of the latest pipeline for a given branch.
Test Results Analysis: Get detailed test metadata without leaving your IDE.
Config Helper: Validate and get recommendations for CircleCI configuration.
Prompt Templates: Generate structured prompts for AI applications.
Project Management: List followed projects and run pipelines.
Workflow Management: Rerun workflows from the start or from failed jobs.
Diff Analysis: Analyze Git diffs against cursor rules.

Use cases of CircleCI MCP Server

Debugging failed builds and analyzing test failures without leaving your IDE.
Quickly checking the status of pipelines and workflows.
Managing and running pipelines with natural language commands.
Validating CircleCI configurations before deployment.
Generating and testing prompt templates for AI applications.
Identifying flaky tests and analyzing test results.

FAQ from CircleCI MCP Server

What is MCP?

MCP stands for Model Context Protocol, a standardized protocol for managing context between LLMs and external systems.
What are the installation options?

You can install the CircleCI MCP Server using NPX or Docker, depending on your environment.
What kind of tasks can I perform with MCP?

You can find build failures, get logs, identify flaky tests, retrieve pipeline statuses, configure CircleCI, and more, all using natural language commands.

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, Windsurf, Copilot, or any MCP supported 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

CircleCI Personal API Token - you can generate one through the CircleCI. Learn more or click here for quick access.

For NPX installation:

pnpm package manager - Learn more
Node.js >= v18.0.0

For Docker installation:

Docker - Learn more

Installation

Cursor

Using NPX

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
      }
    }
  }
}

Using Docker

Add the following to your cursor MCP config:

{
  "mcpServers": {
    "circleci-mcp-server": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "CIRCLECI_TOKEN",
        "-e",
        "CIRCLECI_BASE_URL",
        "circleci:mcp-server-circleci"
      ],
      "env": {
        "CIRCLECI_TOKEN": "your-circleci-token",
        "CIRCLECI_BASE_URL": "https://circleci.com" // Optional - required for on-prem customers only
      }
    }
  }
}

VS Code

Using NPX

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
    },
    {
      "type": "promptString",
      "id": "circleci-base-url",
      "description": "CircleCI Base URL",
      "default": "https://circleci.com"
    }
  ],
  "servers": {
    // https://github.com/ppl-ai/modelcontextprotocol/
    "circleci-mcp-server": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@circleci/mcp-server-circleci"],
      "env": {
        "CIRCLECI_TOKEN": "${input:circleci-token}",
        "CIRCLECI_BASE_URL": "${input:circleci-base-url}"
      }
    }
  }
}

Using Docker

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

{
  // 💡 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
    },
    {
      "type": "promptString",
      "id": "circleci-base-url",
      "description": "CircleCI Base URL",
      "default": "https://circleci.com"
    }
  ],
  "servers": {
    // https://github.com/ppl-ai/modelcontextprotocol/
    "circleci-mcp-server": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "CIRCLECI_TOKEN",
        "-e",
        "CIRCLECI_BASE_URL",
        "circleci:mcp-server-circleci"
      ],
      "env": {
        "CIRCLECI_TOKEN": "${input:circleci-token}",
        "CIRCLECI_BASE_URL": "${input:circleci-base-url}"
      }
    }
  }
}

Claude Desktop

Using NPX

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 locate this file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows: %APPDATA%\Claude\claude_desktop_config.json

Claude Desktop setup

Using Docker

Add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "circleci-mcp-server": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "CIRCLECI_TOKEN",
        "-e",
        "CIRCLECI_BASE_URL",
        "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

Using NPX

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

Using Docker

After installing Claude Code, run the following command:

claude mcp add circleci-mcp-server -e CIRCLECI_TOKEN=your-circleci-token -e CIRCLECI_BASE_URL=https://circleci.com -- docker run --rm -i -e CIRCLECI_TOKEN -e CIRCLECI_BASE_URL 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

Using NPX

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
      }
    }
  }
}

Using Docker

Add the following to your windsurf mcp_config.json:

{
  "mcpServers": {
    "circleci-mcp-server": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "CIRCLECI_TOKEN",
        "-e",
        "CIRCLECI_BASE_URL",
        "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 windsurf: https://docs.windsurf.com/windsurf/mcp

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

Features

Supported Tools

get_build_failure_logs

Retrieves detailed failure logs from CircleCI builds. This tool can be used in three ways:
1. Using Project Slug and Branch (Recommended Workflow):
  - First, list your available projects:
    - Use the list_followed_projects tool to get your projects
    - Example: "List my CircleCI projects"
    - Then choose the project, which has a projectSlug associated with it
    - Example: "Lets use my-project"
  - Then ask to retrieve the build failure logs for a specific branch:
    - Example: "Get build failures for my-project on the main branch"
2. 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"
3. 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 three ways:
1. Using Project Slug (Recommended Workflow):
  - First, list your available projects:
    - Use the list_followed_projects tool to get your projects
    - Example: "List my CircleCI projects"
    - Then choose the project, which has a projectSlug associated with it
    - Example: "Lets use my-project"
  - Then ask to retrieve the flaky tests:
    - Example: "Get flaky tests for my-project"
2. Using CircleCI Project URL:
  - Provide the project URL directly from CircleCI
  - Example: "Find flaky tests in https://app.circleci.com/pipelines/github/org/repo"
3. 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 can be used in two ways:
1. Using text output mode (default):
  - This will return the flaky tests and their details in a text format
2. Using file output mode: (requires the FILE_OUTPUT_DIRECTORY environment variable to be set)
  - This will create a directory with the flaky tests and their details
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 three ways:
1. Using Project Slug and Branch (Recommended Workflow):
  - First, list your available projects:
    - Use the list_followed_projects tool to get your projects
    - Example: "List my CircleCI projects"
    - Then choose the project, which has a projectSlug associated with it
    - Example: "Lets use my-project"
  - Then ask to retrieve the latest pipeline status for a specific branch:
    - Example: "Get the status of the latest pipeline for my-project on the main branch"
2. 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"
3. 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 three ways:
1. Using Project Slug and Branch (Recommended Workflow):
  - First, list your available projects:
    - Use the list_followed_projects tool to get your projects
    - Example: "List my CircleCI projects"
    - Then choose the project, which has a projectSlug associated with it
    - Example: "Lets use my-project"
  - Then ask to retrieve the test results for a specific branch:
    - Example: "Get test results for my-project on the main branch"
2. Using CircleCI URL:
  - 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"
3. 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
- Filter by tests result
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
list_followed_projects

Lists all projects that the user is following on CircleCI. This tool:
1. Retrieves and Displays Projects:
  - Shows all projects the user has access to and is following
  - Provides the project name and projectSlug for each entry
  - Example: "List my CircleCI projects"
The tool returns a formatted list of projects, example output:
```
Projects followed:
1. my-project (projectSlug: gh/organization/my-project)
2. another-project (projectSlug: gh/organization/another-project)
```
This is particularly useful for:
- Identifying which CircleCI projects are available to you
- Obtaining the projectSlug needed for other CircleCI tools
- Selecting a project for subsequent operations
Note: The projectSlug (not the project name) is required for many other CircleCI tools, and will be used for those tool calls after a project is selected.
run_pipeline

Triggers a pipeline to run. This tool can be used in three ways:
1. Using Project Slug and Branch (Recommended Workflow):
  - First, list your available projects:
    - Use the list_followed_projects tool to get your projects
    - Example: "List my CircleCI projects"
    - Then choose the project, which has a projectSlug associated with it
    - Example: "Lets use my-project"
  - Then ask to run the pipeline for a specific branch:
    - Example: "Run the pipeline for my-project on the main branch"
2. Using CircleCI URL:
  - 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"
    - Project URL with branch: "https://app.circleci.com/projects/github/org/repo?branch=main"
  - Example: "Run the pipeline for https://app.circleci.com/pipelines/github/org/repo/123/workflows/abc-def"
3. Using Local Project Context:
  - Works from your local workspace by providing:
    - Workspace root path
    - Git remote URL
    - Branch name
  - Example: "Run the pipeline for my current project on the main branch"
The tool returns a link to monitor the pipeline execution.

This is particularly useful for:
- Quickly running pipelines without visiting the CircleCI web UI
- Running pipelines from a specific branch
rerun_workflow

Reruns a workflow from its start or from the failed job.

The tool returns the ID of the newly-created workflow, and a link to monitor the new workflow.

This is particularly useful for:
- Quickly rerunning a workflow from its start or from the failed job without visiting the CircleCI web UI
analyze_diff

Analyzes git diffs against cursor rules to identify rule violations.

This tool can be used by providing:
1. Git Diff Content:
  - Staged changes: git diff --cached
  - Unstaged changes: git diff
  - All changes: git diff HEAD
  - Example: "Analyze my staged changes against the cursor rules"
2. Repository Rules:
  - Rules from .cursorrules file in your repository root
  - Rules from .cursor/rules directory
  - Multiple rule files combined with --- separator
  - Example: "Check my diff against the TypeScript coding standards"
The tool provides:
- Detailed violation reports with confidence scores
- Specific explanations for each rule violation
Example usage scenarios:
- "Analyze my staged changes for any rule violations"
- "Check my unstaged changes against rules"
This is particularly useful for:
- Pre-commit code quality checks
- Ensuring consistency with team coding standards
- Catching rule violations before code review
The tool integrates with your existing cursor rules setup and provides immediate feedback on code quality, helping you catch issues early in the development process.

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
```

Building Docker Container

You can build the Docker container locally using:

docker build -t circleci:mcp-server-circleci .

This will create a Docker image tagged as circleci:mcp-server-circleci that you can use with any MCP client.

To run the container:

docker run --rm -i -e CIRCLECI_TOKEN=your-circleci-token -e CIRCLECI_BASE_URL=https://circleci.com circleci:mcp-server-circleci

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

CircleCI

Category

Tags

What is CircleCI MCP Server?

How to use CircleCI MCP Server?

Key features of CircleCI MCP Server

Use cases of CircleCI MCP Server

FAQ from CircleCI MCP Server

CircleCI MCP Server

Requirements

Installation

Cursor

Using NPX

Using Docker

VS Code

Using NPX

Using Docker

Claude Desktop

Using NPX

Using Docker

Claude Code

Using NPX

Using Docker

Windsurf

Using NPX

Using Docker

Installing via Smithery

Features

Supported Tools

Development

Getting Started

Building Docker Container

Development with MCP Inspector

Testing