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bgpt-paper-search

搜索科学论文并检索从全文研究中提取的结构化实验数据,通过 BGPT MCP 服务器返回每篇论文的 25+ 个字段,包括方法、结果、样本量、质量评分和结论。适用于文献综述、证据综合以及查找仅凭摘要无法获得的实验细节。

bgpt-paper-search 是什么?

这是一个名为 bgpt-paper-search 的 AI 代理技能,它通过 BGPT MCP 服务器搜索经过整理的科研论文数据库。与传统文献数据库仅返回标题和摘要不同,该技能能够从论文全文中提取结构化数据,包括方法、定量结果、样本量、质量评估以及超过 25 个元数据字段。它特别适用于系统性文献综述、范围界定综述、荟萃分析或临床指南构建中的证据表格汇总,以及跨研究比较实验细节(如效应量、样本量等)。该技能支持远程 MCP 服务器,无需本地安装,可集成到 Claude Desktop、Claude Code 等支持 MCP 协议的代理中。免费层提供每个网络 50 次搜索,付费层每结果 $0.01。使用时,代理通过 MCP 接口调用 `search_papers` 工具,而不是通过 Bash 执行,从而获得高度结构化的论文信息。

兼容平台✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/bgpt-paper-search

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

BGPT Paper Search

概述

BGPT 是一个远程 MCP 服务器,用于搜索由从全文研究中提取的原始实验数据构建的科研论文数据库。与传统文献数据库仅返回标题和摘要不同,BGPT 从实际的论文内容中返回结构化数据——包括方法、定量结果、样本量、质量评估以及每篇论文 25+ 个元数据字段。

何时使用该技能

在以下情况下使用此技能:

  • 搜索具有特定实验细节的科学论文
  • 进行系统性或范围界定文献综述
  • 查找跨研究的定量结果、样本量或效应量
  • 比较不同研究中采用的方法论
  • 寻找带有质量评分或证据分级的研究
  • 需要源自全文论文(不仅仅是摘要)的结构化数据
  • 为荟萃分析或临床指南构建证据表格

设置

BGPT 是一个远程 MCP 服务器——无需本地安装。在使用前,请在代理的 MCP 设置中进行配置;该技能指示代理调用 search_papers MCP 工具,本身并不启用 MCP 访问。

Claude Desktop / Claude Code

添加到您的 MCP 配置中:

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

npm(替代方式)

npx bgpt-mcp

使用方式

一旦 BGPT MCP 服务器配置完毕,可通过代理的 MCP 接口(而非通过 Bash)调用其 search_papers 工具:

搜索关于“CRISPR 基因编辑在人体细胞中的效率”的论文

服务器返回结构化结果,包括:

  • 标题、作者、期刊、年份、DOI
  • 方法:实验技术、模型、方案
  • 结果:包含定量数据的关键发现
  • 样本量:受试者/样本数量
  • 质量评分:研究质量评估
  • 结论:作者的结论和启示

定价

  • 免费层:每个网络 50 次搜索,无需 API 密钥
  • 付费层:使用来自 bgpt.pro/mcp 的 API 密钥,每结果 $0.01

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

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`.

aeon

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.

alphagenome

Look up precomputed AlphaGenome Atlas effects for any GRCh38 single-nucleotide variant (AVI score with Phred and 18 SHAP feature attributions, plus raw and quantile scores for RNA-seq, DNase, ATAC, ChIP-TF, ChIP-histone, CAGE, PRO-cap, splicing, polyadenylation and contact-map tracks), score variants or scan windows on demand with the AlphaGenome model for human and mouse (variant scoring, in silico mutagenesis, REF-versus-ALT track prediction), and build Atlas website deep links. Use when the user mentions AlphaGenome, AlphaGenome Atlas, AVI or AlphaGenome Variant Impact, DeepMind variant effect prediction, or wants to prioritise or mechanistically interpret non-coding, regulatory, splicing, enhancer, promoter, or chromatin-accessibility effects of SNVs from a VCF, credible set, or region. Research use only; not a clinical tool.

analytical-method-validation

Plan, execute, and document validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include

anndata

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

arbor

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g.

arboreto

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

astropy

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

autoskill

Observe the user

benchling-integration

Benchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. Use when automating lab data with benchling-sdk or the v2 API.

bids

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biopython

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.

bioservices

Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.

bulk-rnaseq

End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathway-enrichment), and publication figures (scientific-visualization). Use whenever the user has bulk RNA-seq reads or quant output and wants a complete, reproducible differential-expression workflow — e.g.

cellxgene-census

Query the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. Use when you need population-scale cell metadata, gene expression slices, Census summary counts, source H5AD URIs/downloads, embeddings, spatial Census data, or reference atlas comparisons across organisms, tissues, diseases, assays, and cell types. For analyzing your own local single-cell data use scanpy, anndata, or scvi-tools.

cirq

Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.

citation-management

Comprehensive citation management for academic research. Search OpenAlex, PubMed, and Google Scholar for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.

clinical-decision-support

Prepare and validate research-only clinical decision-support evaluation, evidence-profile, cohort, survival, biomarker/model, privacy, and governance artifacts. Use for aggregate or synthetic research documentation and traceability—not patient care or live clinical operation.

clinical-reports

Create safety-bounded draft structures and run local deterministic checks for clinical case, diagnostic, trial, safety, and aggregate research reports. Use only with synthetic, de-identified, or aggregate inputs and verified source-fact manifests; every output requires qualified review.

cobrapy

Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.

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