"Sequential Thinking and Related Concepts" matching MCP servers:

Enables task management with dependency tracking and workflow orchestration, allowing sequential and parallel execution of tasks with automatic progression and retry logic.

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.

Enables Claude to run structured software development pipelines by directing it through sequential phases, validating evidence before advancing, and persisting state in SQLite for resumption across sessions.

Enables AI assistants to answer questions about nixpkgs packages using nixkeeper's public data, covering outdated versions, Hydra build status and failures, update-bot attempts, related PRs and issues, CVEs, and what needs attention for a maintainer or team. It runs locally over stdio, reads only public data, and requires no account or token.

A Model Context Protocol (MCP) server that provides Xcode-related tools for integration with AI assistants and other MCP clients.

A server that enables fetching and filtering SonarCloud issues related to pull requests, making it easier to identify and fix code quality problems.

Unified capability catalogue with formally verified cartridges, distributed community hosting, and the Teranga menu system for single gateway access to a vast rabbfe of MCP, LSP, NeSy and related servers.!

Enables MCP clients to inspect and manage Semaphore UI automation through its management API, covering projects, templates, tasks, logs, inventories, repositories, and related configuration. It works over stdio or Streamable HTTP with schema-validated tools, read-only mode, project allowlists, and a bounded task-wait helper.

Enables AI assistants to list and retrieve repositories, inspect and create pull requests, and page through related Bitbucket data via Cloud and Server APIs.

Enables AI assistants to interact with Bitbucket repositories, pull requests, and related resources through the Bitbucket Cloud and Server APIs. It supports operations such as listing repositories, retrieving repository details, and fetching or creating pull requests.

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.

Enables AI assistants to interact with Bitbucket Cloud and Server APIs, including listing and retrieving repositories, fetching pull requests, creating pull requests, and managing related resources safely without DELETE operations.

Enables AI assistants to interact with Bitbucket Cloud and Server APIs to list and retrieve repositories, manage pull requests, and access related resources via the Model Context Protocol.

MCP server to lint and validate Kubernetes-related manifests(Helm, FluxCD, ArgoCD, Kustomize, etc.)

Enables AI assistants to interact with Bitbucket Cloud and Server APIs by listing repositories, retrieving repository details, fetching and creating pull requests, and accessing related resources with configurable authentication and pagination.

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

Enables AI assistants to access and manage repositories, pull requests, and related resources via Bitbucket Cloud and Server APIs, including listing repositories, fetching pull request details, and creating pull requests.

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

Enables AI assistants to inspect, query, and diagnose problems in a continuous delivery platform, and to perform release, deployment, runbook, task, tenant, and related operational actions with configurable read-only or write access.

Enables AI assistants to list and retrieve repositories, fetch and create pull requests, and access related resources through Cloud and Server APIs, with pagination and non-destructive operations.

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 Bitbucket Cloud and Server APIs to list and retrieve repositories, fetch and create pull requests, and manage related resources through natural language.

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.

Enables mapping a dependency graph of jobs or tests to reveal parallelizable levels, sequential versus parallel time, critical path, cycle detection, and optional greedy worker schedules.

Enables AI assistants to list and retrieve repositories, fetch and create pull requests, and page through related data via Bitbucket Cloud and Server APIs.

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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.

Enables AI assistants to access and manage repositories, pull requests, and related resources through Bitbucket Cloud and Server APIs.