"A guide to finding people on LinkedIn by their name" matching MCP servers:

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.

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

MCP server for Azure DevOps Server 2022 (on-premises) that enables AI assistants to interact with work items, repositories, builds, and sprints through 29 tools.

MCP server wrapping the full VitoDeploy REST API to manage projects, servers, sites, databases, services, workers, SSL, DNS, and more through any MCP-compatible agent, with 108 tools covering every endpoint.

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

Enables AI agents to deploy, manage, and configure web applications on sota.io, including project creation, deployment, environment variables, custom domains, and rollbacks.

An MCP server designed for React Native and Expo development that provides specialized tools for project scaffolding, architectural best practices, and troubleshooting. It enables AI assistants to guide users through setup, navigation configuration, and CI/CD processes using modern stacks like NativeWind and Zustand.

MCP server for Bitbucket Cloud that enables reviewing, managing, and merging pull requests, assigning reviewers by name, reading files at a ref, and inspecting pipeline status from any MCP client.

Enables natural language interactions with CircleCI through Model Context Protocol, allowing users to retrieve build logs, find flaky tests, check pipeline statuses, and manage workflows without leaving their IDE.

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.

Enables coding agents to build, test, archive, and run iOS apps on a remote Mac fleet from any environment, with XcodeBuildMCP-compatible tools and live simulator access.

Enforces disciplined programming practices by requiring AI assistants to audit their work and produce verified outputs at each phase of development, following structured workflows for refactoring, feature development, and testing.

Enables MCP-compatible AI agents to deploy and manage applications on Google Cloud Run, including service deployment, listing, logging, and project creation.

Turns a manager's plain-English goal into a verified, looped, watchable build run driven by the IDE's agent, without SDK.

Guards PR merge decisions by validating CI, approvals, conflicts, and branch freshness.

Enables AI agents to manage Databricks Lakeflow jobs by building and uploading Python wheels and triggering runs with specific arguments. It provides a structured way to orchestrate complex data experiments and monitor execution directly on Databricks clusters.

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.

Integrates Honeybadger error tracking with Cursor IDE, allowing developers to fetch, analyze, and troubleshoot application errors directly from their development environment.

A dynamic Azure DevOps MCP server that automatically switches authentication context based on the current working directory, enabling seamless integration with multiple Azure DevOps organizations and projects.

Enables AI coding agents to drive developer workflows as BPMN processes on a local CIB seven engine, including starting releases, inspecting runs, and approving human-decision gates via MCP tools.