SPOKEAgent

A structure-aware MCP (Model Context Protocol) server for querying the SPOKE biomedical knowledge graph for rapid biomedical knowledge inference. Points to the official release of SPOKE.

SPOKEAgent doesn't just expose raw Cypher — it understands SPOKE's structure. It introspects the live schema (so it tolerates schema changes), resolves entity names / synonyms / identifiers to canonical nodes via the graph's indexes, profiles a node's real relationships, finds shortest paths between entities, and guards every query against the pitfalls of a 43-million-node graph (case-sensitivity, expensive edges, unbounded scans). See docs/CHANGELOG.md and docs/TEST_FINDINGS.md for the design rationale, validated over 100 natural-language questions through BioRouter.

BioRouter Extension

Download spokeagent.brxt

Drag the .brxt file into BioRouter's Extensions → Add extension dialog. BioRouter will install the virtual environment automatically and prompt for required credentials.

Related MCP server: BioBTree

Features

• Compact, cached schema — a curated node table + Source-[:REL]->Target edge directory with counts and cost flags, derived live from the database.

• Entity resolution — name / synonym / brand / identifier → canonical SPOKE node(s), case- and apostrophe-safe, across DOID / Entrez / Ensembl / DrugBank / UMLS / UBERON / GO, ranked by connectivity.

• Node profiling — a node's real relationship types, directions, and counts.

• Path finding — shortest connecting path(s) between two entities.

• Guarded querying — read-only Cypher with auto safety-LIMIT, transaction timeout, and trimmed output.

Alternative install (custom extension via uvx)

If you prefer not to use the .brxt bundle, you can register SPOKEAgent as a custom extension command:

1. In BioRouter, go to Add custom extension

2. Fill in the extension name and description

3. For the command, use the following:

uvx --from git+https://github.com/BaranziniLab/SPOKEAgent spokeagent

4. Add an environment variable:

   a. Variable name = SPOKEAGENT_PASSCODE

   b. Value = <your-passcode> (from the credentials page)

   c. Click + Add to add the variable.

5. Click Add extension — you're ready to go

Available Tools

The recommended workflow is schema once → resolve_entity → query / describe / find_path, passing string literals through parameters.

1. get_spoke_schema(refresh=false)

Returns a compact, cached map of the current graph: node_labels (by count), an edge_directory of {source, rel, target, count, expensive}, and usage_notes (identifier namespaces, edge properties, vestige filtering, performance rules). Call once near the start of a task.

2. resolve_entity(query, label?, limit?)

Maps a free-text name, synonym, brand, or identifier to canonical node(s). Handles case-sensitivity, apostrophes, and cross-vocabulary identifiers (DOID, Entrez, Ensembl, DrugBank, UMLS CUI, UBERON, GO). Returns ranked candidates {label, name, identifier, matched_on, score, degree}. Use it before querying.

3. describe_node(query, label?)

Returns a node's real relationship profile {dir, rel, neighbor_label, count} — to pick the right edge, or to confirm (and report) that an expected edge is absent instead of guessing more queries.

4. find_path(source, target, source_label?, target_label?, max_hops?, max_paths?)

Resolves both endpoints and returns the shortest connecting path(s) as node + relationship-type sequences — the right tool for "how are X and Y connected".

5. query_spoke(cypher_query, parameters?)

Execute a read-only Cypher query. Behaviour built in: writes rejected; a safety LIMIT auto-applied to unbounded non-aggregate queries; a transaction timeout; trimmed, size-capped output; coaching metadata on empty/limited results.

Example (resolve first, then query by the resolved value via parameters):

MATCH (d:Disease {name: $name})-[:ASSOCIATES_DaG]->(g:Gene)
RETURN g.name AS gene, g.identifier AS entrez
LIMIT 10

parameters = {"name": "Alzheimer's disease"}. Note ASSOCIATES_DaG carries diseases_scores/gwas_pvalue (not a score property), and drug→gene targets go (:Compound)-[:BINDS_CbP]->(:Protein)<-[:ENCODES_GeP]-(:Gene) — there is no TARGETS_CtG edge.

Security

This server enforces read-only access to the SPOKE knowledge graph. Write operations (CREATE, MERGE, DELETE, etc.) are not permitted.

License

MIT

Authors

• Wanjun Gu (wanjun.gu@ucsf.edu)

• Gianmarco Bellucci (gianmarco.bellucci@ucsf.edu)

Editors

• Ilan Ladabaum (ilan.ladabaum@ucsf.edu)

About SPOKE

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.