"How to implement Active Directory authentication in a project" matching MCP servers:

Provides VS Code active editor context (open file, cursor position, selection) to MCP-compatible AI tools.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

A self-contained Claude Code plugin that profiles a project by running a fixed DAG to emit agent-facing context pages, a human/developer guide, and a queryable vectorstore.

Enables AI agents to query a repository's verified semantic model, including capabilities, ownership, contracts, constraints, impact, health, and verification status, without re-deriving project facts. It exposes read-only tools for inspecting, reasoning about, and verifying the provenance-tracked surface.

Security scanner for MCP servers and AI-generated code. Detects leaked API keys, PII, prompt injection, and MCP misconfigs with A-F security grades.

An MCP server that reads any codebase (GitHub repo or local folder) and explains it using AI. Enables users to ask questions about project structure, key files, auth flows, and more in plain language.

MCP server for structured Laravel project planning. Scans projects, creates tickets, and exports as JSON.

A Python framework that exposes developer tools through MCP, REST API, and CLI from a single shared registry, enabling AI assistants, HTTP clients, and terminal users to access the same tools.

MCP server providing diagnostic tools to analyze software architecture, security, REST API compliance, and dependencies for multiple programming languages. Enables AI agents to run scans and audits on codebases.

Indexes Unreal Engine project C++ source, config files, dependencies, gameplay tags, replication, asset references, and log categories into a SQLite database and exposes tools for AI assistants to query structural and config info.

This MCP server automatically analyzes project architecture and finds similar code patterns to maintain consistency across different programming languages.

A Model Context Protocol (MCP) server that enables AI applications to access and analyze local code repositories without manual uploads, providing file listing, content reading, code searching, and project structure analysis capabilities.

Maximizes AI agent context window by enabling compact code reading and editing, reducing tokens by 40% for deeper codebase understanding.

Hardware-accelerated codebase mapping that indexes Git repositories into Postgres/pgvector and serves code search, relationships, and static analysis results via a stdio MCP server.

Read-only MCP server that provides AI agents with context about Unity project relationships, including scenes, prefabs, scripts, GUIDs, and code impact analysis.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables scanning projects for dependency vulnerabilities, secrets, license conflicts, code quality, and git health, returning a 0-100 health score with actionable suggestions.

Provides AI coding agents with fast, deterministic access to code graphs, knowledge lifecycle state, and cross-document symbol links, enabling compact context retrieval and seamless session handoffs.

An MCP server that provides CLI coding agents with persistent decision memory, codebase dependency-graph awareness, plan validation against architectural constraints, and a self-bootstrapping constraints.md file.

Enables AI assistants to manage project analysis, code metrics, documentation, Git operations, code quality, and file organization through natural language commands.