BGPT MCP API

Search scientific papers from any MCP tool. Raw experimental data from full-text papers — methods, results, quality scores. 50 free searches, then $0.01/result.

Documentation

BGPT

Evidence infrastructure for AI

The Evidence Layer for Scientific AI

Give your AI evidence you can verify before you trust its answer.

4,794

new studies added this week

Keep your AI closer to the latest evidence.

Build scientific AI that can show its work.

Search by topic or DOI. Retrieve claims linked to experiments, exact results, scope, limitations, falsification criteria, and source provenance.

When an answer matters, you can trace it back to what each paper actually showed.

50 free results · Then $0.02/result

Try 50 Evidence Records Free Explore the evidence record ↓No sign-up or API key

Check the answer See the experiments and exact results behind each claim.

Trace it to the source Follow evidence to source sections, figures, tables, and text.

See where it stops Keep scope, biases, extraction status, and uncertainty visible.

Built for scientific model training · literature review · RAG · research agents


Quick setup

Get Started in 30 Seconds

Pick your tool, copy the config, and start searching.

Claude Desktop Cursor Claude Code Python API Other

Add to ~/.claude/claude_desktop_config.json:

{ "mcpServers": { "bgpt": { "url": "https://bgpt.pro/mcp/sse" } } }

Copy Config

Add to .cursor/mcp.json in your project root:

Copy Config

Run in your terminal:

claude mcp add bgpt --transport sse https://bgpt.pro/mcp/sse

Copy Command

Traditional HTTP API. No key needed for the first 50 results.

import requests

def search_bgpt(query, num_results=16, days_back=None, api_key=None, output_format="evidence"): payload = { "query": query, "num_results": num_results, "output_format": output_format, } if days_back is not None: payload["days_back"] = days_back if api_key: payload["api_key"] = api_key

response = requests.post(
    "https://bgpt.pro/api/mcp-search",
    json=payload,
    timeout=60,
)
response.raise_for_status()
return response.json()["results"]

papers = search_bgpt("CRISPR delivery neurons", num_results=5) paper = papers[0] print(paper["central_claim"]) if paper["evidence"]["evidence_units"]: unit = paper["evidence"]["evidence_units"][0] print(unit["claim"]) print(unit.get("result", {}).get("reported_statistics", [])) print(unit["provenance"])

Copy Python

Endpoints for any MCP-compatible client:

Endpoints: SSE: https://bgpt.pro/mcp/sse Streamable HTTP: https://bgpt.pro/mcp/stream

Tools:

search_papers query (required) Search terms num_results (optional) 1-100, default 16 days_back (optional) Filter to recent papers output_format(optional) evidence, full, or legacy

lookup_paper doi (required) DOI of the paper output_format(optional) evidence, full, or legacy

Copy


From question to evidence

How It Works

  1. Add the config above to your AI tool
  2. Ask your AI to search, e.g. “Search BGPT for CRISPR delivery methods in neurons” or look up a specific paper by DOI
  3. Get evidence units linking claims to experiments, results, scope, and provenance

Your first 50 results are free. After that, add billing at $0.02/result.


Simple metered access

Pricing

One result is one structured paper record.

Free Tier

$0

  • ✓ 50 free results
  • ✓ Evidence ready for training and RAG
  • ✓ No API key needed

Pay-as-you-go

$0.02 / result

  • ✓ Unlimited searches
  • ✓ Evidence ready for training and RAG
  • ✓ Pay only for returned results Keep Searching for $0.02/Result →

Inspect the record

What BGPT Returns

Use output_format="evidence" for compact records or "full" to add legacy metadata.

Search responses place records in results. DOI lookup places the record in result and includes found. Evidence and full output omit papers without extracted evidence.

Identification

doi: DOI identifier

title: Paper title

publication_date

publication_name: Journal

Claim-Level Evidence

central_claim

evidence.schema_version and extraction_status

evidence.document_type

evidence.evidence_units: claims linked to experiments

claim_type: causal, correlational, mechanistic, descriptive, diagnostic, prognostic, efficacy, or safety

evidence_status: supported, mixed, contradicted, or not_assessable

evidence_basis: direct, indirect, or synthesized

relation_to_central_claim: supports, qualifies, challenges, or independent

experiment: design, independent units, groups, outcomes, and methods

reported_statistics: exact reported value text, comparison, test, and analysis model

applicability.demonstrated_in: demonstrated scope

provenance[]: section, figure, table, exact source text

evidence.record_provenance: source hash, extraction time, truncation status

Scientific Scrutiny

counterevidence_or_ambiguity[]: reported or inferred qualifiers

limitations[]: reported or inferred limits

evidence_units[].falsification_criteria[]: concrete weakening tests with basis

how_to_falsify: concise paper-level criterion

limitations_and_biases: concise paper-level synthesis

Paper-Level Fields in Full Output

sample_size_and_population_characteristics

methods_and_experimental_techniques

results_and_conclusions

experimental_models

software_and_tools_used

code_and_data_links

Additional Fields in Full Output

keywords

lab_name

funding_json

citations_json

reference_count

legacy metadata: retained for existing clients

Coverage reflects the available full text and what the paper reports. Empty optional fields are omitted from compact evidence output. V4 records contain at most 5 evidence units and 2 provenance passages per unit; each passage is at most 320 characters. Older records retain their explicit schema version. extraction_status and any normalization_warnings expose incomplete or repaired records.


Details and support

Frequently Asked Questions

How do I start searching for free?

Just add the config above to your AI tool and start asking questions. No sign-up, no API key needed. You get 50 free results automatically.

What happens when I use up my 50 free results?

How do I start pay-as-you-go?

How do I use my API key?

How does billing work exactly?

What does days_back do?

Where do I find my API key if I lost it?

Can I cancel anytime?

Need help?


Stop taking scientific answers on faith.

Give your AI evidence you can inspect. The first 50 records are free.

Copy your config