"An MCP for extracting and analyzing documentation using AI" matching MCP servers:

AI Gateway - MCP server providing AI-powered tools and automation by MEOK AI Labs

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 acceptance gates for AI coding-agent runs by recording evidence, running deterministic validation, applying a quality gate, and rendering auditable outcomes.

Enterprise-grade MCP server for Jenkins CI/CD integration that enables AI assistants to diagnose build failures, analyze pipelines, and search logs through natural conversation.

Devops AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables intelligent Kubernetes deployments, automated documentation testing, organizational pattern management, and shared prompt libraries. Provides AI-powered recommendations based on cluster capabilities and automates DevOps workflows through conversational interfaces.

Dependency Updater AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

A LAN multi-AI collaborative development ecosystem connecting tools like Cursor, Windsurf, and Claude Desktop via MCP for automated Dev-QA-Ops workflows.

Enables evidence-first release readiness assessment by running or accepting build, API, browser, visual, performance, and security evidence, then returning SHIP, REVIEW, or HOLD recommendations with clustered regressions.

Connects AI coding assistants to GitLab instances, enabling project and issue management, merge request reviews, CI/CD inspection, repository browsing, code search, and local AI-powered features via Ollama.

Enables interaction with Azure DevOps through natural language in Cursor IDE. Supports work item management, pull requests, builds, releases, test management, and guided workflows for development teams, QA testers, and release management.

A remote MCP server that provides AI agents access to the Rootly API for incident management, allowing users to query and manage incidents, alerts, teams, services, and other incident management resources through natural language.

Enables lifecycle-first governance for Edge AI fleets via MCP tools for approval requests, gate evaluation, and manual hold, ensuring deterministic deployment decisions with two-person approval, attestation, and safe rollback.

Enables AI to directly read, edit, and compile PowerBuilder PBL projects.

Enables LLM clients to access DevSecOps tooling such as CI/CD pipeline status, vulnerability triage, log search, and dependency scanning through MCP, turning AI copilots into security-aware engineering partners.

Enables AI clients to analyze software test results and defect records, producing explainable GO, CONDITIONAL_GO, or NO_GO release-readiness recommendations with deterministic risk scoring, failed-test retrieval, defect hotspot ranking, and regression test planning.

MCP server for end-to-end QA automation: generates test scenarios, discovers Playwright locators, creates TypeScript test code, executes tests, and creates GitHub issues for failures.

Automates task delivery by providing tools for running delivery workflows, creating merge requests, updating Jira issues, and generating release notes.

Provides AI assistants with comprehensive access to Azure DevOps services including work items, repositories, pull requests, wikis, builds, pipelines, and test plans through 25+ MCP tools with multi-project support.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.