LLM Agent Framework in ComfyUI includes MCP sever, Omost,GPT-sovits, ChatTTS,GOT-OCR2.0, and FLUX prompt nodes,access to Feishu,discord,and adapts to all llms with similar openai / aisuite interfaces, such as o1,ollama, gemini, grok, qwen, GLM, deepseek, kimi,doubao. Adapted to local llms, vlm, gguf such as llama-3.3 Janus-Pro, Linkage graphRAG

ApeRAG: Production-ready GraphRAG with multi-modal indexing, AI agents, MCP support, and scalable K8s deployment

100% Rust implementation of code graphRAG with blazing fast AST+FastML parsing, surrealDB backend and advanced agentic code analysis tools through MCP for efficient code agent context management

The most accurate and comprehensive Context Engine as a service, optimized for large codebases, powered by advanced GraphRAG and accessible via MCP. It enriches the context for AI agents like Codex, Claude Code, Cursor, etc., making them 35% more efficient and up to 84% faster.

This is a MCP server I built to interact with my hybrid graph rag db.

🏠 An AI real estate app featuring secure auth, conversation management, & personalized property recommendations. Powered by Agentic AI, RAG (w/ Pinecone), GraphRAG (w/ Neo4j), MCP, kNN, K‑Means Clustering, CoT, LangGraph, and a Mixture‑of‑Experts ensemble to deliver accurate, effective, and scalable AI insights. Also features a VS Code extension!

Advanced GraphRAG development with protocol comparison, LLM A/B testing & analytics, and MCP server integration - accessible through web interface and Postman integration

A GraphRAG repository that combines Qdrant (vector search), Neo4j (knowledge graph), and LLMs to provide an end-to-end ingest, query, and generation pipeline with an MCP HTTP server.

An MCP server that uses LightRAG and Tree-sitter to build a repository knowledge graph from code and docs, for Q&A and implementation planning.

MCP-native knowledge graph orchestrator that unifies data silos with GraphRAG, dynamic connectors, and local AI.

MCP server for Obsidian GraphRAG, agent-ready context, preview-only planning, and safe repo handoffs

Personal knowledge graph with entity extraction, GraphRAG, and MCP integration. Turn your notes into searchable intelligence.

🧠 Universal long-term memory for AI agents. GraphRAG-powered knowledge base with vector search + graph traversal. Privacy-first, local-only, MCP-compatible. Connect Claude, Copilot, or any AI assistant.

A unified Neo4j MCP server for GraphRAG: vector search, fulltext search, and search-augmented Cypher queries

GraphRAG, MCP integration, orchestration, evaluation using Azure AI and Microsoft Agent Framework

MCP server that mimics a pure vector database using Neo4j - vector search, fulltext search, NO graph traversal. Designed to compare Vector RAG vs GraphRAG effectiveness. Uses OpenAI embeddings. Built with FastMCP.

This repo is for learning and building GraphRAG MCP servers for agents. Completed during internship at Tesla.

shopping like prompting! An auditable, tool-driven multi-agent architecture for online shopping (Draft Orders, Evidence Snapshots, GraphRAG, MCP).

A ReAct-driven MCP Agent that performs GraphRAG over Neo4j for movie discovery. Translates natural language to Cypher, retrieves subgraphs, and generates explainable recommendations with provenance.

Awesome Boilerplate for RAG | MCP | GraphRag

Integration of Neo4j GraphRag with Salesforce via MCP

GraphRAG-Driven Agentic Reasoning: A Research Prototype using ADK, MCP, and Neo4j

GraphRAG Local Search implementation in Go with OpenAI API and MCP protocol support

GraphRAG-powered MCP server that transforms an Obsidian vault into a semantically queryable knowledge graph.

Production-grade agentic AI system built phase by phase — LangGraph, ChatGroq, MCP, RAG, GraphRAG, Multi-agent, Redis, DeepEval, Docker

AstraOS — The most complete AI agent operating system. Multi-LLM, MCP, A2A, GraphRAG, Computer Use, 14+ channels, 55+ skills, Admin Dashboard, Enterprise-ready. Built in India.

Using MCP (model context protocol) to interact with local files, Extracting structured knowledge from PDFs (and other docs), Ingesting them into Neo4j via GraphRAG, and Supporting intelligent tools like Streamlit LLM assistants

Local-first knowledge engine with semantic search, GraphRAG, and Claude Desktop integration via MCP. Features hybrid search (vector + BM25), cross-encoder reranking, multi-format document ingestion (PDF, DOCX, audio, video), and privacy-preserving PII detection. Apple Silicon optimized.

A comprehensive, AI-powered research assistant that combines Graph Database technology with Retrieval-Augmented Generation (GraphRAG) to provide intelligent document processing, advanced entity extraction, and knowledge graph construction. Features MCP (Model Context Protocol) integration for enhanced document upload and processing capabilities.

OpenShrimp CORA is a next-generation intelligent search and knowledge management platform built upon the CAMEL multi-agent framework. It integrates a MCP architecture, RAG, GraphRAG, and visual prompt engineering to achieve a white-box workflow loop from problem definition to automated execution.