"Using ast-grep to Modify Code Programmatically" matching MCP servers:

Enables whole-program callgraph reachability analysis to locate dead functions and stale flags, and integrates with MCP-compliant clients for automated code review, breaking-change audits, and CI/CD workflow pruning.

Enables coding agents to develop on one machine and verify results on another, using branch-bound runbooks, isolated checkpoints, and structured receipts to guide repair iterations.

An MCP server that adds engineering discipline to AI-assisted development, enforcing evidence-gated TDD, security review, backup strategy, and deployment generation to turn AI-generated code into production-ready software.

Reviews every PR for security, bugs, and performance, then fixes the findings through MCP, keeping you in control of what merges.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

Enables AI assistants to review GitLab merge requests by fetching changes, analyzing diffs, adding comments, and managing approvals through the GitLab API. Supports complete merge request analysis, file-specific reviews, and version comparisons.

MCP server for IBM Code Engine — build, push, and deploy containers from Cursor, Copilot, Claude, and Cline using natural language.

Enables AI-assisted development by running and testing code directly on Databricks clusters via natural language, then deploying Databricks Asset Bundles.

Generates VS Code installation buttons and markdown badges for MCP servers, supporting both Stable and Insiders versions with configurable inputs and commands.

Enables automated AI-powered code review for pull requests across GitHub, GitLab, Bitbucket, and Azure DevOps via webhooks, and manual code review through MCP tools using Groq, Claude, or GPT-4.

RegressGuard is an MCP server that records a known-good baseline and lets AI coding agents detect regressions (broken API contracts, failing tests, schema changes) during their edit loop, allowing them to self-correct before committing.

An MCP server for automated code reviews on Azure DevOps pull requests, enabling AI assistants to fetch PR details, validate requirements, post inline comments, and set review votes.

Enables automated Python code quality checks including linting, complexity analysis, typo detection, structure validation, duplicate detection, and test coverage, with integration into Cursor IDE and CLI.

Enables AI assistants to interact with ArgoCD APIs through standardized MCP tools for managing applications, resources, and deployments.

An MCP server that provides typed, audited, least-privilege tools for monitoring AWS infrastructure and GitHub pipelines, including instance health, service status, logs, deployment status, CI workflow runs, failed jobs, and PR checks.

A three-layer funnel AI code review engine that reduces LLM token consumption by 70%+ while providing deep code analysis. It integrates with GitHub PRs via MCP protocol to automate code review with static analysis, RAG, and LLM-based checks.

MCP server for GitHub Actions CI failure triage. It wraps the gh CLI to fetch PR checks, failed jobs, and tail/grep failed job logs with ANSI/timestamp stripping and root-cause extraction.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

MCP server for CodeRocket Deploy providing AI-generated CI/CD workflows and AI code review as tools inside Claude Code.

Enables AI agents to scan code for security vulnerabilities using multiple static analysis tools, with support for filtering, deduplication, and CI/CD integration.