"Cursor AI SDK and related codebase information" matching MCP servers:

Um servidor MCP completo para integração com Sentry no Cursor, oferecendo 27 ferramentas para monitoramento de erros, performance e saúde de aplicações.

An MCP server that integrates Azure DevOps with Cursor IDE, allowing Claude AI to manage projects, work items, repositories, pull requests, and test plans.

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

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.

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 agents and teams to manage versioned delivery work items, role-tagged handoffs, revision- and source-bound evidence, QA gate evaluation, and release-owner attestations through MCP tools.

Enables AI assistants to deploy and manage hosted apps from git repos, read logs, add Postgres databases and domains, manage API keys and budgets, and send requests to 200+ AI models. Connects over remote Streamable HTTP with OAuth sign-in, so users need no API keys, installs, or local server.

Enables deterministic GitHub issue and pull request delivery workflows, including issue creation, development, verification, PR publication, review, and merge, with strict configuration and admission controls.

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.

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.

Access a 24/7 AI senior developer with 26 specialized tools for the full software development lifecycle. Use tools like explain_code, debug_code, and refactor_code to analyze, debug, and optimize your codebase instantly. Deploy github_fix_issue and create_pr for seamless GitHub automation, or get ai_development_advice for architecture and career guidance.

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.

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

Enables deterministic detection of pytest config-leakage that corrupts agent-benchmark grading, returning CLEAN/CORRUPTED verdicts and corrected pytest commands.