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:

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/stream instead.

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

MCP tool

search_papers

... View full README on GitHub