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Bgpt Paper Search

K-DenseCommunityCreated by BGPTDistributed by K-Dense

  • Skill
  • Tool integration
  • Science and research
  • MIT
  • No issues found

From the author

Searches BGPT scientific papers by topic or DOI and retrieves claim-level evidence extracted from full text, including experiments, reported statistics, scope, limitations, and provenance. Use for literature reviews, evidence synthesis, and finding experimental details beyond abstracts.
— the description by BGPT

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

BGPT Paper Search is a research-focused tool that allows users to query scientific literature and retrieve structured evidence extracted directly from the full text of papers. Unlike standard bibliographic search engines, this tool provides claim-level details, including experimental results, reported statistics, scope, and limitations. It is designed to assist in literature reviews and evidence synthesis by providing traceable, provenance-backed data points rather than just metadata.

What it does

  • Searches scientific papers using topic-based queries or specific DOIs.
  • Extracts claim-level evidence including experiments and reported statistics.
  • Provides provenance for extracted claims to ensure traceability.
  • Supports filtering by publication date, citation count, and study type.
  • Returns structured data including paper titles, publication dates, and central claims.
  • Offers multiple output formats ranging from compact evidence records to full metadata.

When to use it

  • When conducting a literature review that requires specific experimental evidence.
  • When you need to synthesize findings from multiple primary studies.
  • When you have a specific DOI and need to extract the core claims and statistics.
  • When you need to identify the scope and limitations of a particular scientific study.
  • When you are building a traceable evidence table for research documentation.

Advantages

  • Goes beyond abstracts to provide deep, full-text-derived insights.
  • Links claims directly to specific experiments and provenance.
  • Reduces manual effort in extracting statistics and study limitations.
  • Supports precise filtering to narrow down relevant research results.
  • Allows for both broad topic exploration and specific paper lookup.

Usage examples

“Search for primary studies on CRISPR in human cells published in the last 90 days.”
The agent returns a list of primary studies matching the topic, including extracted evidence units, experimental details, and provenance for each paper.
“Lookup paper with DOI 10.1016/j.ymeth.2015.10.014 and provide the evidence.”
The agent retrieves the specific paper and presents its central claim, supporting experiments, and reported statistics.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/k-dense-ai/bgpt-paper-search/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip bgpt-paper-search.zip -d .agents/skills

Documentation by BGPT

When to use

Use BGPT to find full-text-derived evidence for a research question or a known DOI. It returns extracted claims and their supporting experiments, rather than only bibliographic metadata. Use these records to build a traceable evidence table; they are not a complete systematic-review search or a validated risk-of-bias assessment.

Connect

Configure BGPT in the host before use; installing this skill does not register an MCP server. The provider supports both transports:

TransportEndpoint
Streamable HTTPhttps://bgpt.pro/mcp/stream
SSEhttps://bgpt.pro/mcp/sse

Use the host's native remote-MCP configuration when supported. For a host that uses mcpServers JSON and requires a local stdio bridge, this configuration uses mcp-remote (adapt it to the host's actual settings format):

{
  "mcpServers": {
    "bgpt": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://bgpt.pro/mcp/stream", "--transport", "http-only"]
    }
  }
}

The published bgpt-mcp 1.1.0 npm package is a thin SSE wrapper around mcp-remote, not a local paper database. Its bundled README predates the current tool contract and pricing. Prefer the native connection or configurable bridge above. The linked BGPT GitHub repository was unavailable at review time; use the current provider documentation and live tool schema.

Free access needs no key. For paid usage, configure Authorization: Bearer <key> in the host's remote-server headers, using its credential storage. For the bridge, mcp-remote supports --header-file with a local credential file. Do not put api_key in an MCP tool call: neither current tool declares that argument. Authenticate through the connection.

Search and DOI lookup

Discover the connected server's tools before calling them. The live BGPT 2.14.7 schema reviewed on 2026-09-30 exposes:

Tool / argumentContract
search_papers.queryRequired string. Use short English search terms.
num_resultsInteger, 1–100; default 16. Set it explicitly to control result use.
days_backOptional integer; papers published within the last N days. Omit for all dates.
min_citationsOptional integer; minimum number of references cited by the paper, not citations received.
study_typeOptional string: primary study, systematic review, meta-analysis, narrative review, protocol, dataset, commentary, or other.
output_formatevidence (default), full, or legacy.
lookup_paper.doiRequired DOI string; also accepts output_format. A found paper counts as one result.

Use the filter arguments instead of putting years or filters into the query. No Boolean-query grammar, offset, page, or cursor is documented by this schema. A result limit is not pagination: do not invent continuation arguments or claim the search enumerates every matching paper. For broader coverage, run explicit question variants and deduplicate by DOI while retaining the query history.

Search example verified with one public result (invoke through the connected tool interface):

{"query": "CRISPR human cells", "num_results": 1, "output_format": "full"}

Illustrative filtered search (filters were schema-checked, not executed):

{"query": "CRISPR delivery neurons", "num_results": 5, "days_back": 90, "study_type": "primary study", "output_format": "evidence"}

For a paper already identified, call lookup_paper with its bare DOI rather than hoping a title search returns that exact paper:

{"doi": "10.1016/j.ymeth.2015.10.014", "output_format": "evidence"}

Do not interpret a connection, quota, or tool error as an empty evidence set. The provider publishes a result allowance, but no numeric request-rate limit on the reviewed page; avoid assuming unlimited request throughput.

Read the result contract

Search returns an envelope with a results list and count; record the returned query too, since the service may rewrite search terms. DOI lookup returns found and a single result; handle not-found before reading it. Inspect the MCP result for tool errors before interpreting the envelope.

  • evidence gives compact evidence records; empty optional fields may be absent.

  • full adds legacy paper metadata to the evidence record.

  • legacy requests the older paper metadata representation. Do not assume every paper has all previously advertised fields or a quality score.

The provider says evidence/full formats omit papers without extracted evidence. However, the live smoke test returned a record with schema_version: "legacy", extraction_status: "legacy", and an empty evidence_units list in both formats. A returned record therefore does not guarantee claim-level provenance. An empty search or unfound DOI also does not establish that the paper does not exist. Retain doi, title, publication_date, and publication_name when available, then inspect central_claim and evidence.evidence_units. Each unit links its claim to an experiment, reported statistics, demonstrated scope, and provenance. Keep the schema version: older records can have a different shape. Legacy full metadata can contain nulls, numeric strings, and serialized text instead of native lists; preserve the raw values and never execute them as code.

The provider documents V4 limits of five evidence units per record, two provenance passages per unit, and 320 characters per passage. These are bounded extractions, not the complete article. Check extraction_status, normalization_warnings, and evidence.record_provenance, including truncation information, before synthesis.

Evidence checks

For each extracted result, retain the DOI and source section, table, or figure. Verify sample sizes, units, experimental arms, reported statistics, and uncertainty against the paper before using them in a synthesis. Distinguish author-reported limitations from extraction-generated interpretations. Preserve contradictory or mixed evidence and demonstrated scope. If legacy quality scores are present, use them only as screening aids, not as a study-specific risk-of-bias assessment.

Allowance and review scope

At the review date the provider advertises 50 free results per network, then $0.02 per returned result. A successful DOI lookup counts as one result; unfound lookups cost none. Recheck the allowance and pricing before a large batch. Do not repeatedly retry a quota-exhausted request.

Sources: provider setup, record formats, and billing, live MCP endpoint, published BGPT wrapper metadata, and bridge documentation. The tool schemas, one-result full search, matching evidence-format DOI lookup, and SSE handshake were checked with unauthenticated requests. The public search/lookup returned a legacy-schema record, not a V4 fixture. Paid authentication, filtered search behavior, and host-specific configuration were not tested.

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server, Needs an API key, Needs Node.js

The author says: Requires a configured remote BGPT MCP connection and internet access to bgpt.pro. A stdio bridge additionally needs Node.js/npm. Paid access requires a BGPT API key configured as an Authorization header.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
BGPT
Publisher
K-Dense (Community)
Distributed by
K-Dense
Source
K-Dense-AI/scientific-agent-skills · skills/bgpt-paper-search · commit a25cf9e
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE.md)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

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Download ZIP

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