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CircleCI▌

circleci-public

by circleci-public

Connect seamlessly with CircleCI to fetch build failure logs, troubleshoot issues, and streamline your CI/CD workflow.

Enables agents to talk to CircleCI. Fetch build failure logs to fix issues.

github stars

★ 80

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Works directly in your IDENatural language queries to CircleCI9+ specialized tools for CI/CD workflows

best for

  • / Developers debugging failed CI/CD builds
  • / DevOps teams monitoring pipeline health
  • / Engineers investigating test failures

capabilities

  • / Fetch build failure logs and error details
  • / Identify flaky tests across pipeline runs
  • / Check latest pipeline status for branches
  • / Retrieve test results and metadata from jobs
  • / Validate CircleCI configuration files
  • / Trigger new pipelines and rollbacks

what it does

Connects to your CircleCI account to fetch build logs, pipeline status, and test results directly from your IDE or AI assistant.

about

CircleCI is an official MCP server published by circleci-public that provides AI assistants with tools and capabilities via the Model Context Protocol. Connect seamlessly with CircleCI to fetch build failure logs, troubleshoot issues, and streamline your CI/CD workflow. It is categorized under developer tools.

how to install

You can install CircleCI in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

NOASSERTION

CircleCI is released under the NOASSERTION license.

readme

CircleCI MCP Server

License: Apache 2.0 CircleCI npm

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.

Use Cursor, Windsurf, Copilot, Claude, or any MCP-compatible client to interact with CircleCI using natural language — without leaving your IDE.

Tools

ToolDescription
get_build_failure_logsRetrieve detailed failure logs from CircleCI builds
find_flaky_testsIdentify flaky tests by analyzing test execution history
get_latest_pipeline_statusGet the status of the latest pipeline for a branch
get_job_test_resultsRetrieve test metadata and results for CircleCI jobs
config_helperValidate and get guidance for your CircleCI configuration
create_prompt_templateGenerate structured prompt templates for AI applications
recommend_prompt_template_testsGenerate test cases for prompt templates
list_followed_projectsList all CircleCI projects you're following
run_pipelineTrigger a pipeline to run
run_rollback_pipelineTrigger a rollback for a project
rerun_workflowRerun a workflow from start or from the failed job
analyze_diffAnalyze git diffs against cursor rules for violations
list_component_versionsList all versions for a CircleCI component
download_usage_api_dataDownload usage data from the CircleCI Usage API
find_underused_resource_classesFind jobs with underused compute resources

Installation

<details> <summary><strong>Cursor</strong></summary>

Prerequisites:

Using NPX in a local MCP Server

Add the following to your Cursor MCP config:

{
  "mcpServers": {
    "circleci-mcp-server": {
      "command": "npx",
      "args": ["-y", "@circleci/mcp-server-circleci@latest"],
      "env": {
        "CIRCLECI_TOKEN": "your-circleci-token",
        "CIRCLECI_BASE_URL": "https://circleci.com",
        "MAX_MCP_OUTPUT_LENGTH": "50000"
      }
    }
  }
}

CIRCLECI_BASE_URL is optional — required for on-prem customers only. MAX_MCP_OUTPUT_LENGTH is optional — maximum output length for MCP responses (default: 50000).

Using Docker in a local MCP Server

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",
        "-e",
        "MAX_MCP_OUTPUT_LENGTH",
        "circleci/mcp-server-circleci"
      ],
      "env": {
        "CIRCLECI_TOKEN": "your-circleci-token",
        "CIRCLECI_BASE_URL": "https://circleci.com",
        "MAX_MCP_OUTPUT_LENGTH": "50000"
      }
    }
  }
}

Using a Self-Managed Remote MCP Server

Add the following to your Cursor MCP config:

{
  "inputs": [
    {
      "type": "promptString",
      "id": "circleci-token",
      "description": "CircleCI API Token",
      "password": true
    }
  ],
  "servers": {
    "circleci-mcp-server-remote": {
      "url": "http://your-circleci-remote-mcp-server-endpoint:8000/mcp"
    }
  }
}
</details> <details> <summary><strong>VS Code</strong></summary>

Prerequisites:

Using NPX in a local MCP Server

Add the following to .vscode/mcp.json in your project:

{
  "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": {
    "circleci-mcp-server": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@circleci/mcp-server-circleci@latest"],
      "env": {
        "CIRCLECI_TOKEN": "${input:circleci-token}",
        "CIRCLECI_BASE_URL": "${input:circleci-base-url}"
      }
    }
  }
}

💡 Inputs are prompted on first server start, then stored securely by VS Code.

Using Docker in a local MCP Server

Add the following to .vscode/mcp.json in your project:

{
  "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": {
    "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}"
      }
    }
  }
}

Using a Self-Managed Remote MCP Server

Add the following to .vscode/mcp.json in your project:

{
  "servers": {
    "circleci-mcp-server-remote": {
      "type": "sse",
      "url": "http://your-circleci-remote-mcp-server-endpoint:8000/mcp"
    }
  }
}
</details> <details> <summary><strong>Claude Desktop</strong></summary>

Prerequisites:

Using NPX in a local MCP Server

Add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "circleci-mcp-server": {
      "command": "npx",
      "args": ["-y", "@circleci/mcp-server-circleci@latest"],
      "env": {
        "CIRCLECI_TOKEN": "your-circleci-token",
        "CIRCLECI_BASE_URL": "https://circleci.com",
        "MAX_MCP_OUTPUT_LENGTH": "50000"
      }
    }
  }
}

Using Docker in a local MCP Server

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",
        "-e",
        "MAX_MCP_OUTPUT_LENGTH",
        "circleci/mcp-server-circleci"
      ],
      "env": {
        "CIRCLECI_TOKEN": "your-circleci-token",
        "CIRCLECI_BASE_URL": "https://circleci.com",
        "MAX_MCP_OUTPUT_LENGTH": "50000"
      }
    }
  }
}

Using a Self-Managed Remote MCP Server

Create a wrapper script (e.g. circleci-remote-mcp.sh):

#!/bin/bash
export CIRCLECI_TOKEN="your-circleci-token"
npx mcp-remote http://your-circleci-remote-mcp-server-endpoint:8000/mcp --allow-http

Make it executable:

chmod +x circleci-remote-mcp.sh

Then add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "circleci-remote-mcp-server": {
      "command": "/full/path/to/circleci-remote-mcp.sh"
    }
  }
}

To find or create your config file, open Claude Desktop settings, click Developer in the left sidebar, then click Edit Config. The config file is located at:

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

For more information: https://modelcontextprotocol.io/quickstart/user

</details> <details> <summary><strong>Claude Code</strong></summary>

Prerequisites:

Using NPX in a local MCP Server

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

Using Docker in a local MCP Server

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

Using a Self-Managed Remote MCP Server

claude mcp add circleci-mcp-server 

---

FAQ

What is the CircleCI MCP server?
CircleCI is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for CircleCI?
This profile displays 43 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.

Use Cases▌

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

✓

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

✓

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

✓

Complete complex tasks end-to-end without manual steps

Implementation Guide▌

Prerequisites

  • ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • ›Basic understanding of MCP architecture and capabilities
  • ›Access credentials for integrated services (if required)
  • ›Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • ⚠MCP server not loading: Check config syntax, verify installation
  • ⚠Connection errors: Check network, firewall, credentials
  • ⚠Feature not working: Read server docs, check required parameters
  • ⚠Performance issues: Monitor resource usage, check for network latency
  • ⚠Conflicts with other servers: Check port assignments, namespace collisions

Best Practices▌

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • −Don't grant overly permissive access to MCP servers
  • −Don't skip reading security considerations in docs
  • −Don't expose sensitive data without proper controls
  • −Don't run untrusted MCP servers without code review
  • −Don't ignore error messages—investigate root cause

💡 Pro Tips

  • ★Combine multiple MCP servers for powerful workflows
  • ★Create custom MCP servers for your specific needs
  • ★Share successful configurations with team
  • ★Use MCP inspector for debugging
  • ★Join MCP community for tips and troubleshooting

Technical Details▌

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This▌

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration▌

  • →Tool composition: Chain multiple MCP tools in workflows
  • →Context augmentation: Provide AI with relevant external data
  • →Action delegation: Let AI execute tasks on external systems
  • →Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.8★★★★★43 reviews
  • ★★★★★Chaitanya Patil· Dec 8, 2024

    CircleCI has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • ★★★★★Kabir Zhang· Dec 8, 2024

    Strong directory entry: CircleCI surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • ★★★★★Piyush G· Nov 27, 2024

    We evaluated CircleCI against two servers with overlapping tools; this profile had the clearer scope statement.

  • ★★★★★Fatima Choi· Nov 27, 2024

    CircleCI is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • ★★★★★Rahul Santra· Nov 7, 2024

    According to our notes, CircleCI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • ★★★★★Pratham Ware· Oct 26, 2024

    I recommend CircleCI for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • ★★★★★Shikha Mishra· Oct 18, 2024

    We wired CircleCI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • ★★★★★Kabir Khan· Oct 18, 2024

    CircleCI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • ★★★★★Kabir Diallo· Sep 25, 2024

    We wired CircleCI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • ★★★★★William Flores· Sep 13, 2024

    CircleCI is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

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