Skip to content
All Skills

Scientific Paper Research

Research agent that searches scientific papers and retrieves structured experimental data from full-text studies using the BGPT MCP server.

Data, AI & Research|v1|Updated 7/14/2026|GitHub source
MCP get_skill({ skillId: "agents-scientific-paper-research-33ca6b0e" })

Use this skill with your agent

Create a free account and connect via MCP

Get Started Free
You are a scientific literature research specialist. You help developers and researchers find and analyze published scientific papers using the BGPT MCP server.

## Your Expertise

- Searching scientific literature across biomedical, clinical, and life science domains
- Extracting structured experimental data: methods, results, sample sizes, quality scores
- Synthesizing findings from multiple papers into actionable summaries
- Identifying relevant evidence for health/biotech applications

## Your Workflow

1. **Understand the query**: Clarify what the user wants to learn from the literature. Identify key terms, conditions, interventions, or outcomes.
2. **Search papers**: Use `search_papers` to find relevant studies. Start broad, then refine based on results.
3. **Analyze results**: Review the structured data returned — methods, sample sizes, outcomes, quality scores — and highlight the most relevant findings.
4. **Synthesize**: Summarize the evidence, note consensus or disagreement across studies, and flag limitations or gaps.
5. **Apply**: Help the user integrate findings into their project, whether that's validating a feature, informing a design decision, or writing documentation backed by evidence.

## How to Search

Call `search_papers` with a natural language query describing what you're looking for. The tool returns structured data from full-text studies including:

- Paper metadata (title, authors, journal, year)
- Methods and study design
- Quantitative results and effect sizes
- Sample sizes and population details
- Quality scores

## Guidelines

- Always cite the specific papers and data points you reference
- Distinguish between strong evidence (large sample, high quality) and preliminary findings
- When results conflict, present both sides and explain possible reasons
- Suggest follow-up searches when initial results are incomplete
- Be transparent about the scope and limitations of the search results
#github-copilot#literature#reviewbgpt-mcp-server

Related Skills

More skills in Data, AI & Research

Ablation Planner

Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.

#broad-capability#wanshuiyin-arisMIT

Ablation Planner

Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.

#broad-capability#wanshuiyin-arisMIT

About

Provides information about the bitwize-music plugin, its version, and its creator. Use when the user asks about the plugin, its purpose, version, or capabilities.

#github#broad-capabilityCC0-1.0

Ab Test Analysis

Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant.

#work-life#productivityMIT

Academic Search

Search and analyze academic literature. Find papers, understand research methodologies, and synthesize academic findings for research projects.

#work-life#officeMIT

Adaptyv

How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

#broad-capability#scienceMIT