Structured paper understanding for AI
Claims · causal metadata · integrity warnings — for honest citation
DOI is for papers. Citare is for claims.
Citare is a database of claims extracted from peer-reviewed academic papers. Each claim carries causal-strength metadata (design basis, verification status) and integrity warnings (mediator, boundary condition, effect-disappears-under-control), so AI can cite findings honestly.
search_claims
· grouped by paper · live data
claude mcp add --transport http citare https://citare.dev/mcp
https://citare.dev/mcp
mcpServers:"citare": {"transport": "http", "url": "https://citare.dev/mcp"}
codex mcp add citare --url https://citare.dev/mcp --transport http
~/.gemini/settings.json:{"mcpServers": {"citare": {"url": "https://citare.dev/mcp"}}}
https://citare.dev/mcp
/mcp above.https://citare.dev/sse
Extract a paper with the v0.13d prompt and call register_claims.
No auth required. Pydantic schema and the quality gate reject broken extractions.
get_pdf_acquisition_guide() → obtain the PDFget_extraction_prompt() → fetch the v0.13d prompt and run extraction in a sub-agentregister_claims(json_data=<extracted JSON>) → register to the DBsearch_claims(doi=...) → verify the registrationDaily Dropbox backups + WARNING-not-REJECT design make it safe to experiment.
Strategy
— mission, vision, and the commitments that follow
Interaction Design Document
— how LLMs are designed to use Citare
Design Review for Builders
— feedback for those building similar systems
GitHub: citareMCP
— MCP server source
Live API stats (JSON)
Copy any of the snippets below.
claude mcp add --transport http citare https://citare.dev/mcp
https://citare.dev/mcp
After connecting, just chat naturally — like
"look up Edmondson 1999 on psychological safety".
The AI will autonomously call search_claims,
cite_claim, etc.