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Safely query the SPOKE biomedical knowledge graph for structured knowledge inference.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "SPOKEAgent" yet — see the docs or source repo.
Resolve the entities for “aspirin” and “myocardial infarction” in the SPOKE knowledge graph, and return the canonical names and possible matches.
Returns entity resolution results for both terms, including canonical entity names and candidate matches.
Find relationship paths between “BRCA1” and “breast cancer” in SPOKE, and explain the meaning of the paths briefly.
Returns graph paths connecting the entities and a brief explanation of the biomedical relationships.
Construct and safely run a Cypher query to find gene entities related to Alzheimer’s disease, then summarize the results.
Returns safely executed query results, including a list of related genes or a concise summary.
Researchers can use it to query the SPOKE biomedical knowledge graph and inspect relationships among diseases, genes, drugs, and other entities. It is useful for initial knowledge inference and path exploration.
Developers can connect this MCP tool to AI workflows so models can perform entity resolution, schema inspection, and safe querying. This helps reduce risk when working with graph queries directly.
Data analysts can inspect the graph schema first and then find connection paths around specific entities. This helps confirm available fields and relationship types.
It is a structure-aware MCP server for the SPOKE biomedical knowledge graph. It supports entity resolution, schema introspection, path finding, and safe Cypher queries.
It is suited for biomedical knowledge retrieval and inference tasks such as resolving entities, inspecting graph structure, finding paths between entities, and running controlled graph queries.
The provided information does not include installation steps or runtime prerequisites. Please see the source repository for details.
Access and combine biomedical RDF and API data through AI-friendly queries.
Enable AI to query knowledge graphs via SPARQL and return structured results.
Connect a Neo4j knowledge graph to AI assistants for search and read-only queries.
Access biomedical APIs to explore genes, drugs, diseases, and clinical research.
Build routable knowledge graphs on SQLite or Postgres with secure MCP access.
Connect AI to any SPARQL endpoint for querying and updating RDF data.