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alterlab-bgpt-search

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Aktualisiert2. Juli 2026 um 14:17

Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server, returning 25+ fields per paper (methods, results, sample sizes, quality scores, conclusions). Use when running a literature review or evidence synthesis, or when needing experimental details (sample sizes, effect sizes, methods, quality scores) that abstracts alone do not provide. Part of the AlterLab Academic Skills suite.

Installation

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AlterLab-IEU

AlterLab-IEU/AlterLab-Academic-Skills

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SKILL.md

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name	alterlab-bgpt-search
description	Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server, returning 25+ fields per paper (methods, results, sample sizes, quality scores, conclusions). Use when running a literature review or evidence synthesis, or when needing experimental details (sample sizes, effect sizes, methods, quality scores) that abstracts alone do not provide. Part of the AlterLab Academic Skills suite.
allowed-tools	Bash
license	MIT
compatibility	Connects to the BGPT MCP server. Free tier allows 50 free results with no API key; higher volume needs a BGPT API key from bgpt.pro/mcp. Requires network access.
metadata	{"skill-author":"AlterLab","version":"1.0.1","skill-source":"https://github.com/connerlambden/bgpt-mcp"}

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 BGPT when the value is in structured full-text experimental data, not titles/abstracts:

Building evidence tables for a meta-analysis, scoping review, or clinical guideline
Extracting sample sizes, effect sizes, methods, protocols, or conclusions across studies
Comparing methodologies, or filtering papers by quality score / evidence grading

For broad title/abstract discovery use alterlab-pubmed; for real-time web-grounded summaries of recent developments use alterlab-perplexity.

Setup

BGPT is a remote MCP server — no local installation required.

Claude Desktop / Claude Code

Add to your MCP configuration:

{
  "mcpServers": {
    "bgpt": {
      "command": "npx",
      "args": ["mcp-remote", "https://bgpt.pro/mcp/sse"]
    }
  }
}

npm (alternative)

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 free results, no API key required
Paid: $0.02 per result (billed per result actually returned, not per search) with an API key from bgpt.pro/mcp

Complementary Skills

Pairs well with:

alterlab-literature-review — gather structured data with BGPT, then synthesize
alterlab-pubmed — PubMed for broad discovery, BGPT for deep experimental data
alterlab-biorxiv — combine preprint discovery with full-text data extraction
alterlab-pyzotero — manage citations from BGPT search results

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The AlterLab front door and multi-agent launcher — routes a task to the right AlterLab skill(s) when the user invokes the suite without naming one, and for a multi-stage goal (or on the keyword 'alterflow', aliases 'alterresearch' / 'ultralab') it CLARIFIES the goal with a few questions, SELECTS the skills the task needs, and runs a dynamic multi-agent workflow composing them (via alterlab-workflow-orchestration, alterlab-research-pipeline, or alterlab-ssci-orchestrator). Triggers on 'use AlterLab skills', 'which AlterLab skill for X', 'is there an AlterLab skill for…', a multi-stage research goal, 'alterflow …', or any generic AlterLab request where the user does not know skill names. It always asks clarifying questions before executing a multi-step run. Use when someone references AlterLab generically, describes a multi-stage goal, or fires the alterflow keyword; when the user already names a specific skill, defer to that skill directly. Part of the AlterLab Academic Skills suite.

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alterlab-meta-analysis

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Runs quantitative meta-analysis — computes effect sizes (Hedges' g / standardized mean difference, log odds/risk ratios) with their variances, pools them under fixed-effect and random-effects models, quantifies heterogeneity (I-squared, tau-squared, Cochran's Q), draws forest and funnel plots, and tests publication bias (Egger's regression, trim-and-fill) — using statsmodels.stats.meta_analysis in Python or the field-standard R metafor via Rscript. It enforces PRISMA reporting and the random- vs fixed-effect decision. Use when pooling effect sizes across studies, running a systematic review's quantitative synthesis, or assessing heterogeneity and publication bias. For finding and screening the literature prefer alterlab-deep-research; for a single study's statistics prefer alterlab-statistical-analysis. Part of the AlterLab Academic Skills suite.

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alterlab-missing-data

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Handles missing data with principled methods — forces an explicit MCAR / MAR / MNAR mechanism statement, then applies multiple imputation by chained equations (MICE) with Rubin's-rules pooling of estimates and standard errors, or full-information maximum likelihood (FIML) where a likelihood/SEM model applies. Uses statsmodels MICE / MICEData in Python or the field-standard R mice via Rscript, and warns that single (mean/regression) imputation and scikit-learn's IterativeImputer return one completed dataset without Rubin's-rules pooling, so they understate standard errors if used as multiple imputation. Use when a dataset has missing values, when choosing an imputation strategy, or when reporting how missingness was handled. For general modeling on complete data prefer alterlab-statistical-analysis; for latent-variable models with FIML prefer alterlab-sem-psychometrics. Part of the AlterLab Academic Skills suite.

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alterlab-multilevel-models

AlterLab-IEU/AlterLab-Academic-Skills

Fits and reports mixed-effects / multilevel / hierarchical models for clustered, nested, longitudinal, and repeated-measures data — random intercepts and slopes, variance components and the ICC, cross-level interactions, and GLMMs (logistic/Poisson) — using statsmodels MixedLM and bambi (Bayesian on PyMC) in Python, or the field-standard R lme4 / glmmTMB / brms via Rscript. It enforces the reporting items reviews find under-reported: full fixed + random specification, centering, variance components + ICC, estimation method, assumption checks, model comparisons, and effect sizes. Use when data are grouped/nested (students in schools, repeated measures, panel/longitudinal) and the question concerns within- vs between-cluster variation. For general single-level regression prefer alterlab-statsmodels; for panel fixed effects used for causal identification prefer alterlab-causal-inference. Part of the AlterLab Academic Skills suite.

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alterlab-qualitative-analysis

AlterLab-IEU/AlterLab-Academic-Skills

Analyzes qualitative data as a dispatched pipeline module — codebook development, thematic / framework / content analysis, and inter-coder reliability computed correctly (Krippendorff's alpha as primary via the krippendorff package or a bundled stdlib nominal calculator with bootstrap CIs; Cohen's / Fleiss' kappa via statsmodels) with 95% CIs and thresholds (alpha >= .80 reliable, .667-.80 tentative). It BRANCHES by design: coefficient-based ICR for codebook / content-analytic coding, versus consensus-and-reflexivity for reflexive thematic analysis where a statistic is not the right criterion. Supports human-vs-LLM double-coding with an alpha check against a human gold standard. Use when coding interviews or open-ended text, building a codebook, or reporting intercoder reliability. For topic modeling / embeddings / supervised text classification prefer alterlab-text-as-data; for the reflexivity gate prefer alterlab-ssci-reflexivity-gate. Part of the AlterLab Academic Skills suite.

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alterlab-ssci-orchestrator

AlterLab-IEU/AlterLab-Academic-Skills

Coordinates a social-science study through the stage-gated methods pipeline — question then design-gate then measurement-gate then sampling-gate then the right analysis module then inference-gate then reporting — holding a single YAML Design Passport that each gate reads and appends, and enforcing gate order with PASS / WARN / BLOCK semantics (design-gate and inference-gate are fail-closed). It is thin: it routes and holds the artifact, it does not run analysis itself. Use when a researcher describes a whole social-science study end to end, asks to run the methods pipeline or a full methodology review, or wants the design-to-inference workflow coordinated rather than a single step. For a single stage trigger that gate directly (alterlab-ssci-design-gate, -measurement-gate, -sampling-gate, -inference-gate); for multi-agent execution mechanics see alterlab-workflow-orchestration. Part of the AlterLab Academic Skills suite.

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name	alterlab-bgpt-search
description	Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server, returning 25+ fields per paper (methods, results, sample sizes, quality scores, conclusions). Use when running a literature review or evidence synthesis, or when needing experimental details (sample sizes, effect sizes, methods, quality scores) that abstracts alone do not provide. Part of the AlterLab Academic Skills suite.
allowed-tools	Bash
license	MIT
compatibility	Connects to the BGPT MCP server. Free tier allows 50 free results with no API key; higher volume needs a BGPT API key from bgpt.pro/mcp. Requires network access.
metadata	{"skill-author":"AlterLab","version":"1.0.1","skill-source":"https://github.com/connerlambden/bgpt-mcp"}

BGPT Paper Search

Overview

When to Use This Skill

Use BGPT when the value is in structured full-text experimental data, not titles/abstracts:

Building evidence tables for a meta-analysis, scoping review, or clinical guideline
Extracting sample sizes, effect sizes, methods, protocols, or conclusions across studies
Comparing methodologies, or filtering papers by quality score / evidence grading

For broad title/abstract discovery use alterlab-pubmed; for real-time web-grounded summaries of recent developments use alterlab-perplexity.

Setup

BGPT is a remote MCP server — no local installation required.

Claude Desktop / Claude Code

Add to your MCP configuration:

{
  "mcpServers": {
    "bgpt": {
      "command": "npx",
      "args": ["mcp-remote", "https://bgpt.pro/mcp/sse"]
    }
  }
}

npm (alternative)

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 free results, no API key required
Paid: $0.02 per result (billed per result actually returned, not per search) with an API key from bgpt.pro/mcp

Complementary Skills

Pairs well with:

alterlab-literature-review — gather structured data with BGPT, then synthesize
alterlab-pubmed — PubMed for broad discovery, BGPT for deep experimental data
alterlab-biorxiv — combine preprint discovery with full-text data extraction
alterlab-pyzotero — manage citations from BGPT search results