"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.

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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#.

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

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.

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.

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.

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

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.

A code understanding and generation system designed for Galacean Engine that helps LLMs comprehend the engine architecture and generate high-quality engine code based on user intent.

An AST-based MCP server that provides token-efficient codebase skeletons to LLM agents, reducing context token usage by 80-95% by exposing structural information instead of full source files.

Enables AI models to run Stylelint on CSS files and fix linting warnings directly through the Model Context Protocol.

Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.

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

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

Enables semantic code search across codebases with automatic incremental indexing. Searches return relevant code snippets with file paths and line numbers based on natural language queries.

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

Enables mapping JavaScript error stack traces back to original source code, extracting context information to help developers locate and fix issues.