Best use case
BGPT Paper Search is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
## Overview
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?
## Overview
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.
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
- `citation-management` — Manage citations from BGPT search resultsRelated Skills
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Paper Summary & Review Skill
## 功能描述
paper-expert-generator
Generate a specialized domain-expert research agent modeled on PaperClaw architecture. Use this skill when a user wants to create an AI agent that can automatically search, filter, summarize, and evaluate academic papers in a specific research field. Trigger phrases include help me create a paper tracking agent for my field, I want an agent to monitor latest papers in bioinformatics, build me a paper review agent for computer vision, create a PaperClaw-style agent for my domain, generate a domain-specific paper expert agent. The generated agent is a complete OpenClaw agent with all required skills (arxiv-search, semantic-scholar, paper-review, daily-search, weekly-report) fully adapted for the target domain.