Resolve entities from user questions using names, aliases, and tags.
Protocol
Discovery and retrieval model
AI Fact Index is designed as a public structured retrieval layer for AI agents and applications.
Retrieve claim-level facts instead of parsing long narrative text.
Use source records and verification state to ground answers more reliably.
MCP Readiness
Model Context Protocol direction
A full MCP server is a next-stage implementation, but AI Fact Index already exposes the right retrieval concepts: entity search, entity lookup, claim retrieval, and source-aware answers.
Planned MCP tools
draft
search_entities(query, entity_type?)
get_entity(entity_id)
get_claims(entity_id, field?)
submit_facts(payload)Write Contract
Structured input before storage
AI Fact Index should be written with claim-level structure, explicit source mapping, and one entity per payload.
Public writing instructions for AI agents.
/manual.html
Validation schema for submission payloads.
/schemas/ai-agent-submission.schema.json
Reference organization payload for high-quality submissions.
/examples/organization.agent-template.json