"Information on GraphRAG, AutoGen, AG2, Daydream, and HybridRAG" matching MCP servers:

An MCP server that builds a knowledge graph from code and text documents, enabling Q\&A and implementation planning via tools like graph_create, graph_plan, and graph_query.

Enables MCP clients such as Codex and CodeBuddy to operate the Unity Editor, search Unity APIs and game source code, and manage asset libraries through vector and graph retrieval.

Enables AI agents to analyze and diff binaries by driving Ghidra headless or inside its GUI, exposing native reverse-engineering tools such as listing functions and segments, searching strings, decompiling, disassembling, and following cross-references. Ships with a devcontainer and supports local stdio or remote HTTP deployment.

Enables MCP clients to load eight on-demand coding skills and inspect project repositories through bounded, read-only map, search, read, diff, checks, and style tools. It keeps context lean by loading skill bodies only when needed and limiting repository scan and output sizes.

MCP server that provides npm package information for AI agents during TypeScript development.

locidx

Deterministic code-graph (GraphRAG) over your repo for LLM agents — local-first, git-native, zero-infra, served via MCP. Python, TS/JS, Rust, Go, Java, C#.

An MCP server that scans codebases to extract structural information (classes, functions, etc.) with flexible filtering options and outputs in LLM-friendly formats.

Provides GraphRAG code search to AI agents, combining structural code graph traversal with semantic and keyword retrieval so agents can find relevant code without exact name matches.

A code review tool server based on Model Context Protocol (MCP), providing multi-dimensional code review and scoring functions.

Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.

Enables agents to query TypeScript and JavaScript code intelligence—type diagnostics after edits, go-to-definition, references, hover information, and document symbols—through MCP tools.

A lightweight, zero-configuration MCP server for source code analysis with GraphRAG capabilities, enabling structural understanding and efficient code completion from MCP-compatible AI tools.

Enables AI coding agents to inspect Runable projects over MCP, providing read-only access to project information and configuration via Runable's inspector.

Semantic code indexer with GraphRAG knowledge graph. Index your codebase, search in natural language, and expose everything via MCP so AI agents understand architecture — not just files.

https://gopls-mcp.org/ MCP server for golang projects development: Expand AI Code Agent ability boundary to have a semantic understanding and determinisic information for golang projects.

The server facilitates access to Julia documentation and source code through Claude Desktop, allowing users to retrieve information on Julia packages, modules, types, functions, and methods.

Enables Claude Code and other MCP-compatible tools to leverage MeshAI's multi-agent orchestration capabilities for code review, refactoring, debugging, documentation, architecture analysis, and feature development. Automatically selects appropriate AI agents based on task content and works with agents built on LangChain, CrewAI, AutoGen, and other frameworks.

EU AI Act compliance scanner for Python AI agents. Scans, analyzes, and remediates LangChain/CrewAI/AutoGen/OpenAI code across 6 articles with 10 MCP tools including prompt injection detection, risk classification, and fix code generation.

An MCP server for EndstoneMC development, enabling module information queries, code search, plugin template generation, event handling guidance, and development tutorials through natural language.

Enables agents to query information about gems in a Ruby project's Gemfile, including source code and metadata.

Enables MCP clients such as Claude Desktop, Cline, and Cursor to quickly extract information about GitHub repositories, including repository summaries, project directory structures, and file contents.

Enables MCP clients to quickly extract information about GitHub repositories, including repository summaries, project directory structures, and file contents.

Enables AI coding agents and MCP clients to pull real-time language-server data from a running editor instance, including diagnostics, hover/definition/signature and type information, and symbol references with usage context. It also supports workspace-wide symbol renaming, opening files, and command execution, letting agents validate changes without waiting on slow tsc/eslint runs.

Enables MCP clients to extract GitHub repository information, including repository summaries, project directory structures, and file contents.

Enables MCP clients to quickly extract information about GitHub repositories, including repository summaries, project directory structures, and file contents.

Enables MCP clients such as Claude Desktop, Cline, and Cursor to quickly extract information from GitHub repositories, including summaries, directory structure, and file contents.

Enables MCP clients to quickly extract information about GitHub repositories, including repository summaries, project directory structure, and file content.

Enables MCP clients to quickly extract GitHub repository information, including summaries, project directory structures, and file contents.

Enables MCP clients to quickly extract information from GitHub repositories, including repository summaries, project directory structures, and file contents.