"Understanding PRD and MVP concepts" matching MCP servers:

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.

A production-ready template for building Model Context Protocol (MCP) servers in Python, using Docker Compose for containerized development and CI/CD.

Query Prometheus from CLI or any MCP client, with retries, caching, and an optional metrics exporter.

A boilerplate for building FastMCP servers, providing a basic setup for testing, linting, formatting, and publishing to NPM.

Provides Kubernetes deployment intelligence with typed query tools and AI-synthesized risk briefs, enabling users to list workloads, get detailed snapshots, query Prometheus metrics, record deployment history, and generate risk assessments before promoting to production.

Enables AI assistants to interact with Woodpecker CI to debug pipeline failures, analyze build logs, troubleshoot configurations, and perform pipeline and repository actions such as triggering, restarting, canceling, approving, activating, and updating settings.

An open source MCP server empowering SREs with intelligent observability, predictive analytics, and AI-driven automation across Kubernetes, OpenShift, and Tekton environments.

Interact with OneDev for CI/CD spec editing, pull request review, and issue workflow automation etc.

A Model Context Protocol server implementation that allows AI models to interact with and manage Spinnaker deployments, pipelines, and applications through a standardized interface.

A production-ready template for building Model Context Protocol servers in Python, featuring example tools, structured logging, and multiple transport protocols.

Enables AI agents to query build/deploy status and request operations on a self-hosted Docker/Compose deployment platform, with Observer and Operator skills and approval-based write actions.

Provides access to PyTorch CI/CD analytics data including workflows, jobs, test runs, and log analysis through an MCP interface.

A basic MCP server template built with FastMCP framework that provides example tools for echoing messages and retrieving server information. Serves as a starting point for developing custom MCP servers with Docker support and CI/CD integration.

Provides AI assistants with access to Capawesome documentation and Cloud management tools, enabling app, build, and deployment operations via API token authentication.

Mneme exposes a governed Decision Index so MCP clients can propose candidate architectural decisions and query decision state, applicability, and traceability. Proposals remain non-authoritative: accepting or activating protections stays under explicit human control.

Supply-chain gate for AI agent skills and MCP servers: poison-scan tool definitions, hash-pin the vetted set into a lock file and verify drift in CI. truecopy-mcp is a drop-in stdio proxy that filters a live server's tools/list down to its pinned, unmodified, unpoisoned tools.

Generates a daily standup note from GitLab merge request or GitHub pull request state: what is ready to merge, what is blocked, what is stale, and what is waiting on your review. When CI is red it opens the failed job's log and reports the error lines, so the note says why the pipeline failed rather than just that it did.

Agent-readiness scorecard for any MCP server: protocol checks, 0-100 score and actionable findings.

Enables AI coding agents and CI to vet npm dependencies before they reach the lockfile, flagging hallucinated, slopsquatted, or otherwise risky packages with evidence-backed verdicts.