An MCP (Model Context Protocol) server for querying the SPOKE biomedical knowledge graph for rapid biomedical knowledge inference. Points to the official release of SPOKE.
Drag the .brxt file into BioRouter's Extensions → Add extension dialog. BioRouter will install the virtual environment automatically and prompt for required credentials.
| Variable | Required | Default | Description |
|---|---|---|---|
SPOKEAGENT_PASSCODE |
✅ | — | Passcode from the SPOKEAgent credentials page |
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Query SPOKE Knowledge Graph: Execute Cypher queries on the SPOKE biomedical knowledge graph
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Get SPOKE Schema: Retrieve the complete schema of the SPOKE knowledge graph including nodes, relationships, and properties
If you prefer not to use the .brxt bundle, you can register SPOKEAgent as a custom extension command:
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In BioRouter, go to Add custom extension
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Fill in the extension name and description
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For the command, use the following:
uvx --from git+https://github.com/BaranziniLab/SPOKEAgent spokeagent-
Add an environment variable:
a. Variable name =
SPOKEAGENT_PASSCODEb. Value =
<your-passcode>(from the credentials page)c. Click + Add to add the variable.
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Click Add extension — you're ready to go
Execute a read-only Cypher query on the SPOKE biomedical knowledge graph.
Parameters:
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cypher_query(string, required): The Cypher query for biomedical knowledge inference -
parameters(dict, optional): Parameters to pass to the SPOKE query
Example:
MATCH (d:Disease)-[r:ASSOCIATES_DaG]->(g:Gene)
WHERE d.name = "Alzheimer's disease"
RETURN g.name, r.score
LIMIT 10List all nodes, their attributes, and their relationships in the SPOKE biomedical knowledge graph.
Returns: Complete schema including node types, properties, and relationships.
This server enforces read-only access to the SPOKE knowledge graph. Write operations (CREATE, MERGE, DELETE, etc.) are not permitted.
MIT
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Wanjun Gu (wanjun.gu@ucsf.edu)
-
Gianmarco Bellucci (gianmarco.bellucci@ucsf.edu)
- Ilan Ladabaum (ilan.ladabaum@ucsf.edu)
SPOKE (Scalable Precision medicine Oriented Knowledge Engine) is a large-scale biomedical knowledge graph that integrates data from multiple sources to support precision medicine research.