"How to find people on LinkedIn" matching MCP servers:

Helps support engineers find similar GitHub issues to speed up troubleshooting by searching repositories and calculating similarity scores based on issue descriptions.

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.

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

Enables LLMs to list, create, and comment on GitHub issues using your own GitHub identity via stdio transport.

Enables developers to find personalized open-source contributions by analyzing GitHub profiles and matching them with relevant 'good first issues' and beginner-friendly repositories. Provides comprehensive contribution tooling including repository health scoring, setup difficulty assessment, impact estimation, and automated PR planning.

Enables AI assistants to access and analyze GitHub profile data, providing insights on repositories, commit history, coding patterns, and generating portfolio summaries for developers and recruiters.

MCP server for Bitbucket Cloud, focused on pull-request review workflows

An intelligent code version management system based on the MCP protocol, providing AI-enhanced code snapshots, project versioning, and smart change detection for AI-assisted programming.

Makes git commits on behalf of AI by appending "(aider)" to the committer's name, allowing tracking of AI contributions in your codebase.

An MCP server that enables AI agents to retrieve detailed GitHub Pull Request information using git commit hashes, branch names, or PR numbers. It automatically detects repositories and extracts comprehensive PR data including descriptions, labels, and reviews via the GitHub CLI.

Provides natural language search capabilities for Spryker GitHub repositories, packages, and public documentation. It enables code-level searches across Spryker organizations to help developers find relevant modules and technical information.

Enables AI agents to create GitHub issues on explicitly allow-listed repositories using GitHub App authentication, with input validation, rate limiting, and no token exposure.

A modular monolith MCP server connecting multiple providers (Redash, PostgreSQL, GitHub) with unified permission, security, and auditing, enabling secure data access and tool execution.

Enables full-stack compiler development across the hw-native-sys workspace by combining repository operations (git health, code search, task running) with a knowledge layer for architecture docs, task routing, and abstraction/pass pipeline information.

Deterministic, offline root-cause analysis for coding agents: find the commit that introduced a bug, and verify a fix is complete before committing.

A Model Context Protocol server that generates prompts based on Git repository content, including a command to generate PR descriptions from diffs.

An MCP server that enables natural language search capabilities for Spryker packages and code across GitHub repositories, allowing users to find Spryker modules and documentation using conversational queries.

MCP server for on-premises Azure DevOps that lets AI assistants browse repositories, review pull requests, manage work items, and interact with wikis, with NTLM authentication support.

Enables automatic GitHub issue creation from Git diffs. Generates structured issue templates with summaries, technical notes, and appropriate labels based on code changes.

Enables AI agents to safely work on GitHub PR reviews behind a safety boundary, creating draft reviews and optionally submitting them with fixed guardrails, without exposing write tokens.