# AgentCite

> Real, DOI-backed citations for AI agents and content workflows. Given a topic, AgentCite returns the most relevant real peer-reviewed works from openAlex (250M+ records, public-domain CC0), each with a resolvable DOI. It never fabricates a citation — there is no hallucination path. Use it to add verifiable sources to AI-generated content and to satisfy E-E-A-T / factual-grounding requirements.

## What it is
- A REST API and a Model Context Protocol (MCP) server.
- Purpose: replace LLM-hallucinated citations with real, verifiable ones.
- Data source: openAlex (CC0 public domain). Optional openFDA drug-label lookups.

## How an agent uses it
- MCP tool: `get_citations(topic: string, n?: number, since?: number)` → array of real works {title, authors, year, venue, doi, doi_url, cited_by_count}.
- REST: `GET https://agentcite-api.vercel.app/api/cite?topic=<topic>&n=<count>&since=<year>` → JSON {works:[…], markdown:"…"}.

## Endpoints
- Citations: https://agentcite-api.vercel.app/api/cite
- Health: https://agentcite-api.vercel.app/api/health
- Docs: https://agentcite-api.vercel.app/docs.html

## Pricing
- Free: 25 requests/day, no signup (rate-limited by IP).
- Pro: 5,000 requests/day via API key. 7-day free trial, then $19/month, cancel anytime.

## Key facts
- Every returned citation is a real openAlex record with a resolvable DOI.
- Results are relevance-ranked to the query.
- Best for: AI content tools, research agents, SEO/E-E-A-T workflows, anyone whose LLM keeps inventing sources.