"Information about a MCP server with code assistant" matching MCP servers:

Enables auditing codebases for production readiness, including linting, testing, CI/CD, security, branch conventions, architecture, and an A–F quality scorecard via MCP tools.

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 automates CI/CD pipeline creation, analysis, and security enforcement. It generates production-ready pipelines from templates and enforces DevSecOps best practices.

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

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

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 automated testing and coverage reporting for MCP services with test execution, file generation, and mock service creation. Provides comprehensive testing infrastructure including Jest integration, coverage reports, and health checks for the MCP ecosystem.

Enables coding agents and CI/CD pipelines to audit untrusted code by detecting Python sandbox escapes, SQL injection taint, ReDoS regex vulnerabilities, and CORS misconfigurations, while generating Seccomp BPF filters for safer execution.

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.

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.

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 interaction with Azure DevOps services through Personal Access Token authentication. Provides 75 tools for managing work items, builds, repositories, pull requests, and other DevOps operations via both CLI and HTTP API interfaces.

Integrates GitLab with AI assistants to manage merge requests, analyze CI/CD pipelines, and create Architecture Decision Records. It enables seamless code searching, pipeline triggering, and deployment management through the Model Context Protocol.

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.

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.

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.

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.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.