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bgpt-paper-search

搜尋科學論文,並透過 BGPT MCP 伺服器取得從全文研究中提取的結構化實驗資料。每篇論文回傳超過 25 個欄位,包括方法、結果、樣本數、品質評分與結論。適用於文獻回顧、證據綜合,以及尋找僅靠摘要無法獲得的實驗細節。

bgpt-paper-search 是什麼?

此技能讓 AI 代理(如 Claude Desktop / Claude Code)能夠透過 BGPT MCP 伺服器,對一個收錄科學論文的精選資料庫進行高階搜尋。與傳統僅回傳標題與摘要的文獻資料庫不同,BGPT 會從論文的實際內容中提取結構化資料,包括實驗方法、定量結果、樣本數、品質評估等超過 25 個中繼資料欄位。這對於需要詳細實驗數據的系統性文獻回顧、統合分析、臨床指引制定以及方法學比較特別有用。使用者只需在代理程式的 MCP 設定中設定遠端伺服器(網址為 https://bgpt.pro/mcp/sse),即可透過工具呼叫介面(而非 Bash)使用 `search_papers` 工具。此服務提供免 API 金鑰的免費方案(每個網路 50 次搜尋),以及每次結果 0.01 美元的付費方案,非常適合需要深入、結構化論文資料的研究者與開發者。

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

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

BGPT 論文搜尋

概覽

BGPT 是一個遠端 MCP 伺服器,可搜尋一個從全文研究中提取原始實驗資料所建立的精選科學論文資料庫。與傳統僅回傳標題和摘要的文獻資料庫不同,BGPT 會回傳來自論文實際內容的結構化資料——包括方法、定量結果、樣本數、品質評估,以及每篇論文超過 25 個中繼資料欄位。

何時使用此技能

在以下情況使用此技能:

  • 搜尋具有特定實驗細節的科學論文
  • 進行系統性或範圍界定文獻回顧
  • 在不同研究之間尋找定量結果、樣本數或效應量
  • 比較不同研究所使用的方法
  • 尋找附有品質評分或證據等級的論文
  • 需要來自全文論文的結構化資料(不僅是摘要)
  • 為統合分析或臨床指引建立證據表

設定

BGPT 是一個遠端 MCP 伺服器——無需在本機安裝。使用前請先在代理程式的 MCP 設定中進行設定;此技能指示代理程式呼叫 search_papers MCP 工具,本身不會啟用 MCP 存取。

Claude Desktop / Claude Code

請在 MCP 設定中加入以下內容:

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

npm(替代方案)

npx bgpt-mcp

使用方式

一旦 BGPT MCP 伺服器設定完成,即可透過代理程式的 MCP 介面(而非 Bash)呼叫其 search_papers 工具:

搜尋關於「人類細胞中 CRISPR 基因編輯效率」的論文

伺服器會回傳結構化的結果,包括:

  • 標題、作者、期刊、年份、DOI
  • 方法:實驗技術、模型、協定
  • 結果:包含定量數據的主要發現
  • 樣本數:受試者/樣本的數量
  • 品質評分:研究品質評估
  • 結論:作者結論與啟示

價格

  • 免費方案:每個網路 50 次搜尋,無需 API 金鑰
  • 付費方案:每次結果 0.01 美元,需從 bgpt.pro/mcp 取得 API 金鑰

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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