atlas2-mcp/PROJECT.md

atlas2-mcp — project notes

Goal

Implement the atlas2 resolution tool as an MCP server.

Tool contract (resolve)

Based on resolve_scheme.md: 1) Input: resolve("Joe Biden") 2) Cache lookup: alias index + identifier index 3) If hit:

• load RDF -> Python model 4) If miss:
• call Wikidata
• build Entity
• store in RDF
• update cache 5) Return JSON

Where code lives

• app/mcp_server.py — MCP tool registration (resolve)
• app/main.py — FastAPI + HTTP/SSE mount at /mcp
• app/resolve.py — resolve service (currently stubbed)
• app/atlas_store.py — SPARQL persistence (SPARQL endpoint OR Virtuoso MCP tools)

Next steps

1) Replace the stub in app/resolve.py with the cache + resolve flow. 2) Implement alias/identifier indexes. 3) Wire Wikidata calls + RDF storage using atlas_store.py.

Current status

• resolve() basic loop is working end-to-end:
  • store lookup by label/alias
  • Wikidata quick-resolve fallback
  • minimal persist to Virtuoso
  • cache hits return stored results
• Store lookup debug revealed a literal-filter mismatch; lookup is now split into label-first then alias (robust).
• Wikidata resolution switched to the wikidata.reconci.link quick-resolve endpoint for consistent single-candidate resolution.
• Maintenance scaffolding (dry-run CLI) is added:
  • selects atlas:needsCuration true
  • fetches Wikidata entity dump
  • infers Atlas type buckets via ontology/wikidata_subclassof.ttl + keyword matching
  • plans type-specific details (Person/Location today; others via buckets)