bgpt-paper-search
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.
Best use case
bgpt-paper-search is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.
Teams using bgpt-paper-search should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/bgpt-paper-search/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How bgpt-paper-search Compares
| Feature / Agent | bgpt-paper-search | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# BGPT Paper Search
## Overview
BGPT is a remote MCP server that searches a curated database of scientific papers built from raw experimental data extracted from full-text studies. Unlike traditional literature databases that return titles and abstracts, BGPT returns structured data from the actual paper content — methods, quantitative results, sample sizes, quality assessments, and 25+ metadata fields per paper.
## When to Use This Skill
Use this skill when:
- Searching for scientific papers with specific experimental details
- Conducting systematic or scoping literature reviews
- Finding quantitative results, sample sizes, or effect sizes across studies
- Comparing methodologies used in different studies
- Looking for papers with quality scores or evidence grading
- Needing structured data from full-text papers (not just abstracts)
- Building evidence tables for meta-analyses or clinical guidelines
## Setup
BGPT is a remote MCP server — no local installation required.
### Claude Desktop / Claude Code
Add to your MCP configuration:
```json
{
"mcpServers": {
"bgpt": {
"command": "npx",
"args": ["mcp-remote", "https://bgpt.pro/mcp/sse"]
}
}
}
```
### npm (alternative)
```bash
npx bgpt-mcp
```
## Usage
Once configured, use the `search_papers` tool provided by the BGPT MCP server:
```
Search for papers about: "CRISPR gene editing efficiency in human cells"
```
The server returns structured results including:
- **Title, authors, journal, year, DOI**
- **Methods**: Experimental techniques, models, protocols
- **Results**: Key findings with quantitative data
- **Sample sizes**: Number of subjects/samples
- **Quality scores**: Study quality assessments
- **Conclusions**: Author conclusions and implications
## Pricing
- **Free tier**: 50 searches per network, no API key required
- **Paid**: $0.01 per result with an API key from [bgpt.pro/mcp](https://bgpt.pro/mcp)
## Complementary Skills
Pairs well with:
- `literature-review` — Use BGPT to gather structured data, then synthesize with literature-review workflows
- `pubmed-database` — Use PubMed for broad searches, BGPT for deep experimental data
- `biorxiv-database` — Combine preprint discovery with full-text data extraction
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