BGPT MCP Server
Search scientific papers with structured experimental data extracted from full-text studies. Returns 25+ fields per paper including methods, results, sample sizes, limitations, and quality scores.
Documentation
BGPT MCP + REST API
Search scientific papers from Claude, Cursor, any MCP-compatible AI tool, or plain Python.
BGPT is a remote Model Context Protocol (MCP) server and traditional JSON/HTTP API that gives AI assistants and Python apps access to a database of scientific papers built from full-text studies. Unlike typical search tools that return titles and abstracts, BGPT extracts raw experimental data — methods, results, conclusions, quality scores, sample sizes, limitations, and 25+ metadata fields per paper.
Quick Start
Use BGPT from Python, REST, or an MCP client — no API key required for the free tier (50 free results).
Option A: Python / REST API
Call the HTTP API directly from any Python script or notebook:
import requests
def search_bgpt(query, num_results=10, days_back=None, api_key=None):
payload = {"query": query, "num_results": num_results}
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=30,
)
response.raise_for_status()
return response.json()["results"]
papers = search_bgpt("CRISPR delivery neurons", num_results=5)
print(papers[0]["title"])
Option B: Remote MCP Connection
Most modern MCP clients support direct remote connections. BGPT offers two transports:
| Transport | Endpoint |
|---|---|
| SSE | https://bgpt.pro/mcp/sse |
| Streamable HTTP | https://bgpt.pro/mcp/stream |
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"bgpt": {
"url": "https://bgpt.pro/mcp/sse"
}
}
}
Cursor (.cursor/mcp.json):
{
"mcpServers": {
"bgpt": {
"url": "https://bgpt.pro/mcp/sse"
}
}
}
Claude Code (CLI):
claude mcp add bgpt --transport sse https://bgpt.pro/mcp/sse
Cline / Roo Code / Windsurf — same config:
{
"mcpServers": {
"bgpt": {
"url": "https://bgpt.pro/mcp/sse"
}
}
}
Tip: If your client supports Streamable HTTP, you can use
https://bgpt.pro/mcp/streaminstead.
Option C: Via npx (for clients that need a local command)
{
"mcpServers": {
"bgpt": {
"command": "npx",
"args": ["-y", "bgpt-mcp"]
}
}
}
Option D: Install globally
npm install -g bgpt-mcp
Then add to your MCP config:
{
"mcpServers": {
"bgpt": {
"command": "bgpt-mcp"
}
}
}
Any MCP Client
Connect to either endpoint:
SSE: https://bgpt.pro/mcp/sse
Streamable HTTP: https://bgpt.pro/mcp/stream
That's it. No Docker, no build step.
What You Get
BGPT exposes the same scientific-paper search through an MCP tool and a REST endpoint.
REST endpoint
POST https://bgpt.pro/api/mcp-search
| JSON field | Type | Required | Description |
|---|---|---|---|
query | string | Yes | Search terms (e.g. "CRISPR gene editing efficiency") |
num_results | integer | No | Number of results to return (1-100, default 10) |
days_back | integer | No | Only return papers published within the last N days |
api_key | string | No | Your Stripe subscription ID for paid access |
MCP tool
search_papers
| Parameter | Type | Required | Description |
|---|---|---|---|
query | string | Yes | Search terms (e.g. "CRISPR gene editing efficiency") |
num_results | integer | No | Number of results to return (1-100, default 10) |
days_back | integer | No | Only return papers published within the last N days |
api_key | string | No | Your Stripe subscription ID for paid access |
What comes back
Each paper result includes 25+ fields, extracted from the full text:
- Title & DOI — standard identifiers
- Methods — experimental design, techniques used
- Results — raw findings, measurements, statistical outcomes
- Conclusions — what the authors determined
- Quality scores — methodological rigor assessment
- Sample sizes — participant/specimen counts
- Limitations — acknowledged weaknesses
- And more — funding, conflicts of interest, study type, etc.
Example
Ask your AI assistant:
"Search for recent papers on CAR-T cell therapy response rates"
BGPT returns structured experimental data your AI can reason over — not just a list of titles.
Pricing
| Tier | Cost | Details |
|---|---|---|
| Free | $0 | 50 free results, no API key needed |
| Pay-as-you-go | $0.02/result | Billed per result returned. Get an API key at bgpt.pro/mcp |
How It Works
Your AI Assistant (Claude, Cursor, etc.)
│
│ MCP Protocol (SSE or Streamable HTTP)
▼
BGPT MCP / REST API
https://bgpt.pro/mcp/sse
https://bgpt.pro/mcp/stream
https://bgpt.pro/api/mcp-search
│
│ search_papers(query, ...)
▼
BGPT Paper Database
(full-text extracted data)
│
▼
Structured Results
(methods, results, quality scores, 25+ fields)
BGPT is a hosted remote service — your MCP client connects via SSE or Streamable HTTP, or your app calls the REST endpoint directly. No Docker, scraping, or local index required.
Use Cases
- Literature reviews — Ask your AI to survey a topic with real experimental data
- Python notebooks — Pull recent paper evidence into analysis workflows with one HTTP call
- Evidence synthesis — Ground AI responses in actual study findings
- Research assistance — Find papers by methodology, outcome, or recency
- Fact-checking — Verify claims against published experimental results
- Grant writing — Quickly gather supporting evidence for proposals
Configuration Reference
Server Details
| Field | Value |
|---|---|
| Protocol | MCP (Model Context Protocol) |
| Transport | SSE (Server-Sent Events) or Streamable HTTP |
| SSE Endpoint | https://bgpt.pro/mcp/sse |
| Streamable HTTP Endpoint | https://bgpt.pro/mcp/stream |
| REST Endpoint | https://bgpt.pro/api/mcp-search |
| Authentication | None required (free tier) / Stripe API key (paid) |
Full MCP Client Config
{
"mcpServers": {
"bgpt": {
"url": "https://bgpt.pro/mcp/sse"
}
}
}
Documentation
Full documentation, FAQ, and setup guides: bgpt.pro/mcp
OpenAPI spec for the REST endpoint: openapi.yaml
Additional REST discovery assets:
apis.json— machine-readable API discovery metadatallms.txt— AI-crawler and agent-friendly product contextAGENTS.md— integration guidance for AI agentsUSE_CASES.md— RAG, systematic review, notebook, and dashboard use casesPROMPT_GALLERY.md— ready-to-use prompts for scientific RAG, agents, integrity checks, and visual demosCITATION.cffandcodemeta.json— research-software metadataexamples/bgpt_rest_python.py— Pythonrequestsexampleexamples/bgpt_rest_javascript.mjs— JavaScriptfetchexampleexamples/bgpt_rest_curl.sh— cURL exampleexamples/bgpt_plotly_evidence_dashboard.py— Plotly evidence dashboard demoexamples/postman_collection.json— importable Postman collection
Support
- Email: [email protected]
- Issues: GitHub Issues
- API Key / Billing: bgpt.pro/mcp
Contributing
See CONTRIBUTING.md for guidelines on reporting bugs, requesting features, and contributing.
License
This repository (documentation, examples, and configuration files) is licensed under the MIT License.
The BGPT MCP API service itself is operated by BGPT and subject to its own terms of service.