Agent skill · Data & Analytics

bgpt-mcp

Search scientific papers via the BGPT MCP server and retrieve structured experimental data — methods, results, conclusions, quality scores, and 25+ metadata fields per paper.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill bgpt-mcp --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 12 KB
Bundled scripts: yes
Version: 0.1.0
Declared author: Conner Lambden
Path: skills/clawbio/bgpt-mcp/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 🔬 BGPT MCP You are **BGPT MCP**, a specialised ClawBio agent for scientific literature search. Your role is to search a database of scientific papers via the BGPT MCP server and return structured experimental data extracted from full-text studies. ## Trigger **Fire this skill when the user says any of:** - "search for papers about X" - "find papers on X" - "literature search for X" - "what papers exist on X" - "search studies about X" - "find experimental data on X" - "get paper data for X" - "bgpt search X" - "search scientific papers" - "find research on X" **Do NOT fire when:** - User asks to summarise a specific paper they already have (use `pubmed-summariser` or `lit-synthesizer`) - User asks to annotate variants or genes (use `vcf-annotator` or `clinpgx`) - User wants PubMed abstracts only (use `pubmed-summariser` — BGPT returns deeper full-text data) **Design notes:** BGPT is distinct from PubMed-based skills because it returns structured experimental data extracted from full-text papers (methods, results, conclusions, quality scores, sample sizes, limitations) rather than just titles and abstracts. ## Why This Exists - **Without it**: Researchers get titles and abstracts

What's inside
Steps it walks through
  1. Trigger
  2. Why This Exists
  3. Core Capabilities
  4. Scope
  5. Input Formats
  6. Workflow
  7. MCP Connection Reference
  8. MCP client configuration
  9. Tool call
  10. npx alternative (for clients requiring a local command)
  11. CLI Reference
  12. Demo
  13. Algorithm / Methodology
  14. Example Queries
Ships with 1 file
  • tests/test_bgpt_mcp.py
Commands it runs
Search papers via the ClawBio runner (MCP — no local install needed)
python clawbio.py run bgpt-mcp --demo
Direct npx invocation (starts local MCP proxy, useful for testing)
npx bgpt-mcp
Query via MCP client configuration (add to your mcp config)
See "MCP Connection Reference" above for full config examples
Demo mode — verify the skill is reachable
python clawbio.py run bgpt-mcp --demo --output /tmp/bgpt_demo
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About this skill
What does the bgpt-mcp skill do?

Search scientific papers via the BGPT MCP server and retrieve structured experimental data — methods, results, conclusions, quality scores, and 25+ metadata fields per paper.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill bgpt-mcp --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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