CircleCI is a continuous integration and delivery platform that helps developers build, test, and deploy code quickly and efficiently. It automates the software development process, allowing teams to deliver high-quality software at scale.
Integrates with CircleCI to retrieve build failure logs and identify flaky tests. Supports accessing logs via CircleCI URLs or local project context, and analyzing test execution history to detect unreliable tests in a project's test suite.
This MCP server lets you use Cursor IDE, or any MCP Client enabled agent, to use natural language to accomplish things with CircleCI, e.g: Find the latest failed pipeline on my branch and get logs
16
18,899 npm
93
Apache 2.0
Why this server?
Enables interaction with CircleCI pipelines and workflows, providing tools for retrieving build failure logs, identifying flaky tests, checking pipeline status, analyzing test results, validating CircleCI configurations, running and rerunning pipelines, and performing rollbacks.
Enables natural language interactions with CircleCI through Model Context Protocol, allowing users to retrieve build logs, find flaky tests, check pipeline statuses, and manage workflows without leaving their IDE.
13
18,899 npm
Apache 2.0
Why this server?
Allows running MegaLinter linting within CircleCI pipelines.
Security auditor for CI ecosystems that detects supply-chain and injection flaws in CI/CD configuration files across seven CI platforms, providing taint analysis, remediation, and compliance scoring.
2
MIT
Why this server?
Integrates CircleCI workflow tasks into mise for CI/CD pipeline management.
AI-powered MCP server that analyzes project structures to create optimized task architectures for mise, enabling intelligent task management, dependency mapping, and automated task suggestions.
10
MIT
Why this server?
Provides tools for reviewing CircleCI configurations, including retrieving actual configs, validating YAML, analyzing bottlenecks, workflow health, and dependency graphs.
A CircleCI MCP server specialized in config review, providing tools for fetching actual configs, validating changes, and analyzing workflow bottlenecks, health, and DAG dependencies.
5
MIT
Why this server?
Runs test layers through CircleCI to verify changes, with optional CI gating to enforce test success before proceeding.
From ticket to reviewed pull request, on your own machine
2
78 PyPI
330
MIT
Why this server?
Exposes an API-compatible replica of the CircleCI surface as part of the simulated olympus-labs data set, so agents can exercise CircleCI-shaped requests read-only without test accounts or cleanup.
Enables AI agents to read realistic, coherent data—repos, pull requests, issues, commits, users—through API-compatible, read-only replicas of 21 developer platforms including GitHub, Jira, Linear, Slack, Sentry and Salesforce, all preloaded with one simulated company so integrations can be built and tested with no accounts, credentials, rate-limit worry, or cleanup.
10
266 npm
MIT
Why this server?
Enables triggering XenoCI remote macOS builds from CircleCI using the XenoCast CLI and an API key secret.
