# bgpt-paper-search

> Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server, returning 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions.

**Use case**: Extract structured experimental data from full-text papers

**Canonical URL**: https://agentcookbooks.com/skills/bgpt-paper-search/

**Topics**: claude-code, skills, science, scientific-writing

**Trigger phrases**: "search BGPT for papers", "find experimental data on", "get study details for", "extract methods from papers on"

**Source**: [K-Dense AI](https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/scientific-skills/bgpt-paper-search)

**License**: MIT

---

## What it does

`bgpt-paper-search` is a Claude Code skill from K-Dense AI's [scientific-agent-skills repo](https://github.com/K-Dense-AI/scientific-agent-skills). It turns Claude into a structured data extractor for scientific literature by connecting to the BGPT MCP server at [bgpt.pro/mcp](https://bgpt.pro/mcp). Unlike abstract-only searches, BGPT returns 25+ structured fields per paper extracted from full text: methods, results, sample sizes, effect sizes, quality scores, and conclusions.

A session produces a structured dataset of study characteristics — the kind of extraction table that takes hours to build manually for a systematic review or evidence synthesis project.

## When to use it

Reach for it when:

- You're building an evidence synthesis and need structured methods/results tables, not just abstracts
- You want to compare sample sizes, outcome measures, or statistical approaches across a set of studies on the same topic
- You need quality scores or risk-of-bias indicators as part of a systematic review workflow

When *not* to reach for it:

- Simple abstract retrieval or DOI lookup — `paper-lookup` is faster and doesn't require the MCP server
- Broad exploratory searches where you don't yet know what structured fields you need

## Install

Copy the `SKILL.md` from K-Dense AI's [bgpt-paper-search folder](https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/scientific-skills/bgpt-paper-search) into `.claude/skills/bgpt-paper-search/` in your project. This skill requires the BGPT MCP server to be configured — see [bgpt.pro/mcp](https://bgpt.pro/mcp) for setup instructions.

Trigger phrases: "search BGPT for papers", "find experimental data on", "extract methods from papers on".

## What a session looks like

A typical session has three phases:

1. **Query design.** Specify the topic, intervention, population, or outcome of interest. The more specific the query, the more useful the structured extraction.
2. **BGPT retrieval.** Claude calls the BGPT MCP server, which returns papers with full structured extraction — each paper as a record with 25+ fields rather than a flat text block.
3. **Synthesis output.** Claude organizes the extracted records into a comparison table or narrative synthesis, with sample sizes, methods, and findings side by side.

## Receipts

**Where it works well:**
- Biomedical RCTs and observational studies where BGPT's extraction models are trained — structured fields are reliably populated
- Evidence synthesis projects where manual extraction would take a research assistant days

**Where it backfires:**
- Basic science papers and preprints outside BGPT's training distribution may return incomplete field coverage
- The MCP server adds a dependency that must be set up separately — not a zero-configuration skill

**Pattern that works:** use `paper-lookup` to get a candidate set first, then pass the DOI list to `bgpt-paper-search` for structured extraction rather than querying cold.

## Source and attribution

Skill authored by the BGPT team. The canonical SKILL.md lives in the [`bgpt-paper-search` folder](https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/scientific-skills/bgpt-paper-search) of K-Dense AI's scientific-agent-skills repository.

License: MIT. Install, adapt, and redistribute with attribution preserved.

This page documents the skill from a practitioner's perspective. For the formal spec and any updates, defer to the source repo.