General
bgpt-paper-search - Claude MCP Skill
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.
SEO Guide: Enhance your AI agent with the bgpt-paper-search tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to searches bgpt scientific papers by topic or doi and retrieves claim-level evidence extracted from fu... Download and configure this skill to unlock new capabilities for your AI workflow.
Documentation
SKILL.md# BGPT Paper Search
## 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:
| Transport | Endpoint |
| --- | --- |
| Streamable HTTP | `https://bgpt.pro/mcp/stream` |
| SSE | `https://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):
```json
{
"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](https://bgpt.pro/mcp/) 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`](https://github.com/punkpeye/mcp-remote#custom-headers)
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 / argument | Contract |
| --- | --- |
| `search_papers.query` | Required string. Use short English search terms. |
| `num_results` | Integer, 1–100; default 16. Set it explicitly to control result use. |
| `days_back` | Optional integer; papers published within the last N days. Omit for all dates. |
| `min_citations` | Optional integer; minimum number of **references cited by the paper**, not citations received. |
| `study_type` | Optional string: `primary study`, `systematic review`, `meta-analysis`, `narrative review`, `protocol`, `dataset`, `commentary`, or `other`. |
| `output_format` | `evidence` (default), `full`, or `legacy`. |
| `lookup_paper.doi` | Required 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):
```json
{"query": "CRISPR human cells", "num_results": 1, "output_format": "full"}
```
Illustrative filtered search (filters were schema-checked, not executed):
```json
{"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:
```json
{"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](https://bgpt.pro/mcp/),
[live MCP endpoint](https://bgpt.pro/mcp/stream),
[published BGPT wrapper metadata](https://registry.npmjs.org/bgpt-mcp/latest),
and [bridge documentation](https://github.com/punkpeye/mcp-remote).
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.Signals
Information
- Repository
- K-Dense-AI/claude-scientific-skills
- Author
- K-Dense-AI
- Last Sync
- 11/1/2026
- Repo Updated
- 11/1/2026
- Created
- 5/28/2026
Reviews (0)
No reviews yet. Be the first to review this skill!
Related Skills
CLAUDE
Claude-Mem: AI Development Instructions
cursorrules
CrewAI Development Rules
firecrawl-build-onboarding
Get Firecrawl credentials and SDK setup into a project. Use when an application needs `FIRECRAWL_API_KEY`, when an agent should add Firecrawl to `.env`, when the user wants to authenticate Firecrawl for app code, or when choosing the first SDK and docs for a new Firecrawl integration. This skill includes its own browser auth flow, so it does not depend on the website onboarding skill.
firecrawl-build
Integrate Firecrawl into application code whenever a product, agent, or workflow needs web data inside the app — web search, live search results, page scraping, structured extraction, or browser interaction. Use when building any feature that needs data from the web in code, even if the user does not mention Firecrawl explicitly and only describes wanting web data, website content, search, scraping, or interaction in an application. Trigger for Firecrawl requests, "fire girl" shorthand, and generic app-level web-data needs that should map to `/scrape`, `/search`, or `/interact`. Do not use this skill for one-off terminal-only web tasks during the current session; use `firecrawl/cli` for those.
Related Guides
Bear Notes Claude Skill: Your AI-Powered Note-Taking Assistant
Learn how to use the bear-notes Claude skill. Complete guide with installation instructions and examples.
Mastering tmux with Claude: A Complete Guide to the tmux Claude Skill
Learn how to use the tmux Claude skill. Complete guide with installation instructions and examples.
OpenAI Whisper API Claude Skill: Complete Guide to AI-Powered Audio Transcription
Learn how to use the openai-whisper-api Claude skill. Complete guide with installation instructions and examples.