MCP server
by circleci-public
Connect seamlessly with CircleCI to fetch build failure logs, troubleshoot issues, and streamline your CI/CD workflow.
Connects to your CircleCI account to fetch build logs, pipeline status, and test results directly from your IDE or AI assistant.
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.
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.
NOASSERTION
CircleCI is released under the NOASSERTION license.
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
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
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
Share your MCP server with the developer community
CircleCI has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: CircleCI surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We evaluated CircleCI against two servers with overlapping tools; this profile had the clearer scope statement.
CircleCI is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, CircleCI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
I recommend CircleCI for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We wired CircleCI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
CircleCI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We wired CircleCI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
CircleCI is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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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.
| Tool | Description |
|---|---|
get_build_failure_logs | Retrieve detailed failure logs from CircleCI builds |
find_flaky_tests | Identify flaky tests by analyzing test execution history |
get_latest_pipeline_status | Get the status of the latest pipeline for a branch |
get_job_test_results | Retrieve test metadata and results for CircleCI jobs |
config_helper | Validate and get guidance for your CircleCI configuration |
create_prompt_template | Generate structured prompt templates for AI applications |
recommend_prompt_template_tests | Generate test cases for prompt templates |
list_followed_projects | List all CircleCI projects you're following |
run_pipeline | Trigger a pipeline to run |
run_rollback_pipeline | Trigger a rollback for a project |
rerun_workflow | Rerun a workflow from start or from the failed job |
analyze_diff | Analyze git diffs against cursor rules for violations |
list_component_versions | List all versions for a CircleCI component |
download_usage_api_data | Download usage data from the CircleCI Usage API |
find_underused_resource_classes | Find jobs with underused compute resources |
Prerequisites:
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_URLis optional — required for on-prem customers only.MAX_MCP_OUTPUT_LENGTHis optional — maximum output length for MCP responses (default: 50000).
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"
}
}
}
}
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"
}
}
}
Prerequisites:
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.
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}"
}
}
}
}
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"
}
}
}
Prerequisites:
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"
}
}
}
}
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"
}
}
}
}
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:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonFor more information: https://modelcontextprotocol.io/quickstart/user
</details> <details> <summary><strong>Claude Code</strong></summary>Prerequisites:
claude mcp add circleci-mcp-server -e CIRCLECI_TOKEN=your-circleci-token -- npx -y @circleci/mcp-server-circleci@latest
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
claude mcp add circleci-mcp-server
---
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ 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.