"Understanding Code Relationships or Dependencies" matching MCP servers:

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

A zero-dependency Node.js playground for debugging how MCP clients authenticate to an MCP server over HTTP.

Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.

Builds rich code graphs from TypeScript/NestJS codebases using AST analysis and Neo4j, enabling semantic search, natural language querying, and intelligent graph traversal to provide deep contextual understanding of code relationships and dependencies.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

Gemini-powered MCP server for automated code review, analysis, and documentation.

Renders source code as beautiful SVG or PNG images with syntax highlighting, line numbers, and diff support. Ideal for AI agents to present code visually to humans or for sharing snippets.

An MCP server for intelligently reading Java source code, supporting extraction from Maven dependencies and local projects with dual decompilers.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

An MCP server that indexes source code into a local database and provides tools for querying code symbols, dependencies, and tree structure for JavaScript/TypeScript, Java, and Python.

Turns AI assistants into full-stack software engineers with 36 tools for cognitive reasoning, code validation, project scaffolding, and AI/IDE configuration generation across 130+ programming languages, databases, and frameworks.

A comprehensive MCP server that provides AI assistants with tools for file system management, Git integration, and shell command execution. It features specialized code utilities for analysis, formatting, and linting to enhance development workflows within Claude Desktop.

Persistent project memory + architectural decisions + pre-execution safety hooks for Claude Code. Local-only storage, multi-repo workspace, automatic knowledge extraction via background auditor.

Enables AI assistants to surgically extract and analyze code, reducing token usage and costs by up to 200x compared to reading entire files.

A local, SQLite-backed code index for Claude Code, exposed over MCP, enabling targeted code retrieval without external APIs.

Provides tools for AI-driven development workflows including file system operations, code analysis, code execution, web fetching, and search.

Gives AI coding agents persistent memory by storing observations, decisions, and learnings in a local SQLite database with vector search, full-text search, and a rules engine.

Enables AI coding agents to verify code patches locally with sub-50ms neuro-symbolic analysis, detecting structural issues like dependency cycles and interface drift without consuming output tokens.