Your AI agent just hit a wall.
It needs to look up a chemical compound for a drug interaction check. Or find the latest papers on transformer architectures. Or pull US Census demographics for a market analysis. What does it do?
It hallucinates.
Training data is months or years old. Web searches return noisy HTML, not structured data. And the agent has no way to verify what it "knows" against the actual source of record. For any task that requires factual accuracy — scientific, medical, legal, demographic — the agent is guessing.
This is a solvable problem.
The Research Gap in Agent Infrastructure
Look at what the agent ecosystem has built so far: payment rails, wallet provisioning, DeFi integrations, compute access, communication protocols. These are all critical. But there's a missing layer that nobody's talking about.
Knowledge access.
When a human researcher needs to verify a claim, they check PubMed. When they need a chemical structure, they check PubChem. When they need citation data, they check Crossref. When they need demographic trends, they check the Census Bureau.
AI agents have no equivalent. They're making consequential decisions — medical summaries, investment research, compliance checks, scientific literature reviews — without access to the same authoritative sources that human experts rely on.
That's the gap we just filled.
What We Built
We added a full Research & Reference category to the Spraay x402 gateway — 23 endpoints spanning 7 research domains, all accessible via micropayment (USDC on Base or Solana).
Here's what an agent can now look up on demand:
Language & Definitions — word definitions, synonyms, antonyms, phonetics, and pronunciation audio across 9 languages. The foundation for any agent that processes or generates natural language.
Academic Papers — search across 250 million scholarly works spanning every discipline: physics, biology, computer science, economics, social sciences, humanities, engineering, medicine, law, education. Filter by field, year, author, or ORCID. Pull citation graphs. Track what's trending.
Preprints — the bleeding edge of science. 2.4 million preprints across physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, and economics. These are the papers that haven't been published yet — the ones that move markets and shift research directions.
Scholarly Metadata — 150 million published works with full metadata: journal articles, books, conference papers, and datasets. Citation counts, reference lists, journal info by ISSN. When an agent needs to verify a source exists and check its impact, this is the endpoint.
Chemistry — 110 million chemical compounds with molecular structures, physical properties, safety and toxicity data, and biological assay results. Structural similarity search for finding related compounds. This is the same database that pharmaceutical researchers and chemists use daily.
Biomedical Literature — 36 million papers covering medicine, pharmacology, genomics, neuroscience, public health, and more. Related article discovery for any given paper. When your agent is summarizing medical research or checking drug interactions, this is the authoritative source.
Demographics & Government Data — US Census data by state, county, and zip code: population, income, housing, education, employment. Plus the entire federal open data catalog — transportation, climate, health, agriculture, energy, and crime statistics.
The Endpoint Map
# Dictionary & Language
GET /api/v1/research/dictionary/define $0.001
GET /api/v1/research/dictionary/synonyms $0.001
GET /api/v1/research/dictionary/phonetics $0.001
# Academic Papers (250M+ works)
GET /api/v1/research/papers/search $0.002
GET /api/v1/research/papers/by-doi $0.001
GET /api/v1/research/papers/by-author $0.002
GET /api/v1/research/papers/citations $0.002
GET /api/v1/research/papers/trending $0.002
# Preprints (2.4M+ papers)
GET /api/v1/research/preprints/search $0.002
GET /api/v1/research/preprints/by-id $0.001
GET /api/v1/research/preprints/recent $0.002
# Scholarly Metadata (150M+ works)
GET /api/v1/research/scholarly/search $0.002
GET /api/v1/research/scholarly/by-doi $0.001
GET /api/v1/research/scholarly/citations-count $0.001
GET /api/v1/research/scholarly/journal-info $0.001
# Chemistry (110M+ compounds)
GET /api/v1/research/chemistry/compound $0.002
GET /api/v1/research/chemistry/similarity $0.002
GET /api/v1/research/chemistry/bioactivity $0.002
# Biomedical (36M+ papers)
GET /api/v1/research/biomedical/search $0.002
GET /api/v1/research/biomedical/by-pmid $0.001
GET /api/v1/research/biomedical/related $0.002
# Demographics & Government Data
GET /api/v1/research/demographics/census $0.001
GET /api/v1/research/demographics/datasets $0.001
Every response returns a unified JSON envelope with the source, license info, attribution, and a consistent result structure — regardless of which domain the query hits. One integration, every domain.
Where the Demand Is
These aren't hypothetical use cases. This is what agents are already trying to do, badly, with web scraping and hallucination:
Pharmaceutical & biotech agents — compound lookup, drug interaction screening, literature review across 36M biomedical papers. An agent advising on drug safety needs PubChem and PubMed, not a Google search.
Academic writing assistants — paper discovery, citation graph traversal, related work identification. Every grad student's AI assistant needs structured access to the scholarly record.
Market research agents — Census demographics for TAM sizing, government datasets for industry analysis, trend tracking across academic publications for emerging technology identification.
Fact-checking and verification — DOI lookup confirms a source actually exists. Citation counts indicate impact. Cross-referencing preprints against published papers catches retractions and updates.
Scientific monitoring — agents that watch arXiv daily for new preprints in specific categories, track citation velocity on key papers, and flag when a trending paper crosses a threshold.
Compliance and regulatory — biomedical literature search for adverse event signals, chemical safety data for REACH/GHS compliance, demographic data for fair lending analysis.
The pattern is the same in every case: the agent needs structured, authoritative, verifiable data — not a web search result. And it needs it on demand, per call, without managing API keys and parsing 7 different response formats.
One Gateway, Every Domain
The value proposition for agent builders is simple: integrate once with Spraay, and your agent gets access to the same research infrastructure that universities and pharmaceutical companies use. Pay per call. No subscriptions, no rate limit negotiations, no format wrangling.
The research endpoints sit alongside 115 existing endpoints on the gateway covering payments, DeFi, oracle, compute, communication, and more — 138 total across 34 categories. If your agent needs to look something up and take action on what it finds, the entire stack is already wired together.
The gateway is live at gateway.spraay.app. The MCP server on Smithery has all the tools pre-wired for Claude, GPT, and any MCP-compatible agent framework.
Docs: docs.spraay.app
GitHub: plagtech/spraay-x402-gateway
Twitter: @Spraay_app
Agents that know things make better decisions than agents that guess. Give yours a library card.
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