bgpt-paper-search
BGPT Paper Search queries a curated database of scientific papers to retrieve structured experimental data extracted from full-text studies, returning 25+ fields including methods, results, sample sizes, and quality scores. Use this skill for systematic literature reviews, evidence synthesis, meta-analyses, and extracting quantitative experimental details that extend beyond abstract-level information.
git clone --depth 1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills /tmp/bgpt-paper-search && cp -r /tmp/bgpt-paper-search/skills/bgpt-paper-search ~/.claude/skills/bgpt-paper-searchSKILL.md
# 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 resultsCloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Browse the web for any task — research topics, read articles, interact with web apps, fill forms, take screenshots, extract data, and test web pages. Use whenever a browser would be useful, not just when the user explicitly asks.
AI驱动的综合健康分析系统，整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。
Access AlphaFold's 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.