flexible-graphrag MCP Server
stevereiner/flexible-graphrag
[](https://agentrank-ai.com/tool/stevereiner--flexible-graphrag/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) Python, LlamaIndex, LangChain, 15 Property Graph, 4 RDF , 10 Vector, OpenSearch, Elasticsearch DBs. 14 data sources, 10 auto sync: Alfresco, Nuxeo, etc. KG auto-building, Ontologies, LLMs, Docling, LlamaParse, LiteParse, GraphRAG, RAG, Hybrid Search, AI Chat. TypeScript React, Vue, Angular frontends, REST, MCP Server. Options: Langflow, CocoIndex
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
stevereiner/flexible-graphrag is a Python MCP server licensed under Apache-2.0. Python, LlamaIndex, LangChain, 15 Property Graph, 4 RDF , 10 Vector, OpenSearch, Elasticsearch DBs. 14 data sources, 10 auto sync: Alfresco, Nuxeo, etc. KG auto-building, Ontologies, LLMs, Docling, LlamaParse, LiteParse, GraphRAG, RAG, Hybrid Search, AI Chat. TypeScript React, Vue, Angular frontends, REST, MCP Server. Options: Langflow, CocoIndex Topics: alfresco, graphrag, knowledge-graph, llamaindex, rag, mcp-server, arcadedb, docling, falkordb, hybrid-search, neo4j, llamaparse, langchain, ladybugdb, document-processing, ai-chat, ai-context-management, langflow, liteparse, nuxeo.
Ranked #3010 out of 24846 indexed tools.
Ecosystem
Score Breakdown
192 stars → growing community
Last commit 17d ago → recently updated
17/21 issues closed → responsive maintainer
2 contributors → solo project
No dependents → no downstream usage
39 weekly installs → early adoption
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
How to Improve
Matched Queries
From the README
# Flexible GraphRAG
<p align="center">
<a href="./screen-shots/langflow/langflow-sharepoint-graphdb-neo4j.png">
</a>
</p>
<p align="center"><em>Langflow pipeline mode — a SharePoint auto-sync data source (MS Graph delta query) ingesting and targeting Qdrant vector, Elasticsearch, Neo4j, and Graphwise Ontotext GraphDB, with ontology-mode, AI chat drawing context from all four.</em></p>
<p align="center">
<a href="./images/flexible-graphrag-v0.8.0-architecture.png">
</a>
</p>
<p align="center"><em>Can use 1 of 3 ingest pipelines with same configured data sources and database targets, with same UI and same REST / MCP APIs</em></p>
**Flexible GraphRAG** is an open source AI context platform supporting a document processing pipeline (Docling, LlamaParse, or LiteParse), knowledge graph auto-building, ontologies, schemas, many LLM providers, GraphRAG and RAG, hybrid semantic search (fulltext, vector, property graph, RDF/SPARQL), AI query, and AI chat. The backend is **P Read full README on GitHub → Get the weekly AgentRank digest
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