GraphRAG
GraphRAG MCP provides a hybrid retrieval system that combines Neo4j graph database and Qdrant vector database capabilities for powerful document search and context expansion. Developed by Riley Lemm, this server implementation enables semantic search through document embeddings, graph-based context expansion following relationships, and hybrid search combining both approaches. The server exposes tools for querying documentation and resources for accessing database schema information, making it particularly valuable for applications requiring both semantic relevance and structural context in document retrieval, such as technical documentation systems, knowledge bases, or any application needing contextually aware information retrieval.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/rileylemm/graphrag_mcp
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve GraphRAG from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.