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This enables discovery of papers that traditional abstract-based search engines miss because the experimental details are buried in methods sections.","intents":["Find papers that used a specific experimental technique or methodology I'm considering","Discover papers with similar experimental datasets or protocols to my research","Locate papers describing particular lab procedures or measurement approaches without knowing the paper title","Search for papers by experimental outcome or data characteristics rather than topic keywords"],"best_for":["PhD students and academic researchers conducting literature reviews focused on methodology","Researchers in experimental sciences (biology, chemistry, physics) seeking methodological precedent","Teams building custom research workflows that need programmatic access to methodology-level insights"],"limitations":["Limited to papers in the indexed corpus — likely smaller than PubMed or Google Scholar's coverage","Full-text extraction quality depends on PDF parsing accuracy; scanned or poorly-formatted papers may be indexed incompletely","No ranking by citation count or impact factor — results ordered by relevance alone","Search results may include papers where experimental data appears in supplementary materials, not main text"],"requires":["MCP client compatible with Claude or other LLM platforms","Internet connection to reach hosted MCP server","No API key or authentication for free tier (50 searches)"],"input_types":["text query (natural language description of experimental approach or methodology)"],"output_types":["structured data (paper metadata: title, authors, DOI, abstract, relevance score)","text (snippets of matching experimental sections from papers)"],"categories":["search-retrieval","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_bgpt-mcp__cap_1","uri":"capability://tool.use.integration.mcp.server.integration.for.programmatic.research.access","name":"mcp server integration for programmatic research access","description":"Exposes the paper search capability as a Model Context Protocol (MCP) server, allowing LLM agents and custom applications to call search functions directly within their tool-use workflows. The MCP integration handles request serialization, response formatting, and context passing between the client (Claude, custom agents) and the hosted search backend, enabling researchers to embed paper discovery into multi-step research automation pipelines without managing HTTP calls or authentication.","intents":["Integrate paper search into an LLM agent that autonomously researches a topic and synthesizes findings","Build a custom research workflow that searches papers, extracts data, and generates literature reviews","Query papers programmatically from a research assistant tool without managing API keys or rate limits","Chain paper search results into downstream analysis or synthesis tasks within an agent loop"],"best_for":["Developers building LLM agents that need to autonomously search and synthesize academic literature","Research teams automating literature review pipelines with Claude or compatible LLM platforms","Non-technical researchers using Claude with MCP to extend its research capabilities"],"limitations":["MCP server availability and uptime depend on hosted infrastructure — no self-hosted option mentioned","Latency for each search query includes network round-trip to hosted server; not suitable for real-time interactive use cases requiring sub-second response","No built-in caching or result persistence — each search query hits the backend independently","Limited to 50 free searches per user/session; no clear quota management or rate-limiting details for programmatic access"],"requires":["MCP-compatible client (Claude, or custom MCP client implementation)","Network connectivity to hosted BGPT MCP server","Understanding of MCP protocol and tool-use patterns in LLM frameworks"],"input_types":["MCP tool call with search query parameters (text)"],"output_types":["structured JSON (paper metadata, relevance scores, experimental data snippets)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_bgpt-mcp__cap_2","uri":"capability://search.retrieval.zero.authentication.free.tier.search.access","name":"zero-authentication free-tier search access","description":"Provides 50 free searches without requiring account creation, API key registration, or authentication. The system likely uses IP-based or session-based quota tracking to enforce the 50-search limit per user, allowing immediate access for casual researchers and students without onboarding friction. This is implemented as a hosted service with no client-side authentication, making it accessible from any MCP-compatible client or web interface.","intents":["Quickly search for papers without signing up for an account or managing credentials","Evaluate the tool's search quality and coverage before committing to a paid plan","Access research tools as a student or casual researcher without institutional affiliation or payment","Prototype a research workflow without API key management overhead"],"best_for":["Students and casual researchers exploring academic literature without institutional access","Developers prototyping research automation tools before committing to paid APIs","Teams evaluating BGPT as a research tool before purchasing a subscription"],"limitations":["50-search quota is restrictive for serious researchers conducting comprehensive literature reviews","No clear upgrade path or pricing information for additional searches after free tier exhaustion","IP-based or session-based quota tracking may be circumvented or reset; no persistent user identity","Free tier may have lower priority on server resources compared to paid users"],"requires":["No API key or account creation","Internet connection to hosted BGPT server","MCP client or web browser"],"input_types":["text query (no authentication payload)"],"output_types":["structured data (paper results with quota remaining)"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_bgpt-mcp__cap_3","uri":"capability://data.processing.analysis.experimental.data.extraction.and.indexing.from.pdfs","name":"experimental data extraction and indexing from pdfs","description":"Parses scientific paper PDFs to extract and index experimental methodology, protocols, datasets, results, and findings at a granular level beyond abstracts. The system likely uses PDF text extraction, section detection (via heuristics or ML), and possibly named entity recognition to identify experimental parameters, measurements, and procedures. These extracted sections are then indexed in a searchable database, enabling queries that match on methodological similarity rather than keyword overlap.","intents":["Search for papers that used a specific lab technique or measurement apparatus","Find papers with similar experimental parameters or dataset characteristics","Discover papers describing particular statistical methods or data analysis approaches","Locate papers by experimental outcome or result characteristics"],"best_for":["Experimental scientists (biology, chemistry, physics) seeking methodological precedent and reproducibility","Meta-researchers analyzing experimental practices across a field","Teams building systematic reviews focused on methodology rather than outcomes"],"limitations":["PDF extraction quality varies; scanned papers, multi-column layouts, and embedded images may be parsed incorrectly","Section detection heuristics may misclassify supplementary materials or appendices as main experimental data","Extraction does not handle complex tables or figures well — structured data in images is likely missed","No explicit handling of supplementary materials or data repositories linked from papers","Indexing latency means newly uploaded papers may not be searchable immediately"],"requires":["PDF files of scientific papers in the indexed corpus","Sufficient computational resources for PDF parsing and NLP processing at scale"],"input_types":["PDF (scientific paper)"],"output_types":["structured data (extracted experimental sections, metadata, indexed fields)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_bgpt-mcp__cap_4","uri":"capability://search.retrieval.semantic.relevance.ranking.for.experimental.queries","name":"semantic relevance ranking for experimental queries","description":"Ranks search results based on semantic similarity between the user's query and extracted experimental data sections, rather than simple keyword matching or citation counts. The system likely uses embeddings (vector representations of text) to compare the user's methodological description with indexed experimental sections, returning papers where the experimental approach most closely matches the query intent. This enables finding papers with similar methodologies even if they use different terminology.","intents":["Find papers using similar experimental approaches even if they use different terminology","Rank papers by methodological relevance rather than citation count or publication date","Discover papers where the experimental technique is described differently but achieves similar goals","Identify papers with comparable experimental parameters or dataset characteristics"],"best_for":["Researchers seeking methodological precedent across different fields or terminology domains","Teams conducting systematic reviews where methodology matters more than citation impact","Researchers exploring alternative experimental approaches to their own work"],"limitations":["Semantic ranking depends on embedding model quality; may miss papers with novel or non-standard experimental descriptions","No explicit ranking by citation count, impact factor, or recency — may surface obscure papers over well-known ones","Embedding-based ranking is less interpretable than keyword matching; unclear why a paper ranked highly","Semantic similarity may conflate papers with similar methodology but different scientific validity or rigor"],"requires":["Embedding model (likely pre-trained transformer-based model like BERT or similar)","Vector database or similarity search infrastructure to compute relevance scores"],"input_types":["text query (natural language description of experimental approach)"],"output_types":["ranked list of papers with relevance scores"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":42,"verified":false,"data_access_risk":"high","permissions":["MCP client compatible with Claude or other LLM platforms","Internet connection to reach hosted MCP server","No API key or authentication for free tier (50 searches)","MCP-compatible client (Claude, or custom MCP client implementation)","Network connectivity to hosted BGPT MCP server","Understanding of MCP protocol and tool-use patterns in LLM frameworks","No API key or account creation","Internet connection to hosted BGPT server","MCP client or web browser","PDF files of scientific papers in the indexed corpus"],"failure_modes":["Limited to papers in the indexed corpus — likely smaller than PubMed or Google Scholar's coverage","Full-text extraction quality depends on PDF parsing accuracy; scanned or poorly-formatted papers may be indexed incompletely","No ranking by citation count or impact factor — results ordered by relevance alone","Search results may include papers where experimental data appears in supplementary materials, not main text","MCP server availability and uptime depend on hosted infrastructure — no self-hosted option mentioned","Latency for each search query includes network round-trip to hosted server; not suitable for real-time interactive use cases requiring sub-second response","No built-in caching or result persistence — each search query hits the backend independently","Limited to 50 free searches per user/session; no clear quota management or rate-limiting details for programmatic access","50-search quota is restrictive for serious researchers conducting comprehensive literature reviews","No clear upgrade path or pricing information for additional searches after free tier exhaustion","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:29.714Z","last_scraped_at":"2026-04-05T13:23:42.561Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=bgpt-mcp","compare_url":"https://unfragile.ai/compare?artifact=bgpt-mcp"}},"signature":"qn4PqHpUnDr380RrRFWYLZZ541B7Rg/XwZgyjnem5ytcIsShw/4L2Gyo8OSt6b/8mGTeJgMdkBCGhIIUZy0PDQ==","signedAt":"2026-06-19T20:24:48.963Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/bgpt-mcp","artifact":"https://unfragile.ai/bgpt-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=bgpt-mcp","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}