{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"smithery_qustxuhao-paper-search-mcp","slug":"qustxuhao-paper-search-mcp","name":"paper-search-mcp","type":"mcp","url":"https://github.com/QustXuHao/paper-search-mcp","page_url":"https://unfragile.ai/qustxuhao-paper-search-mcp","categories":["mcp-servers"],"tags":["mcp","model-context-protocol","smithery:QustXuHao/paper-search-mcp"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"smithery_qustxuhao-paper-search-mcp__cap_0","uri":"capability://search.retrieval.semantic.paper.search","name":"semantic paper search","description":"This capability utilizes a model-context-protocol (MCP) architecture to enable semantic search across academic papers. By indexing papers and their metadata, it allows users to query using natural language, returning relevant results based on contextual understanding rather than keyword matching. The integration of MCP facilitates seamless communication between the search engine and various data sources, enhancing the search experience.","intents":["How can I find relevant academic papers on a specific topic using natural language?","What are the most cited papers in my field of research?","Can I retrieve papers based on their abstracts or keywords?"],"best_for":["researchers looking for academic literature efficiently","students needing quick access to relevant papers"],"limitations":["Performance may degrade with large datasets due to indexing overhead","Requires internet access for external paper databases"],"requires":["Python 3.8+","Access to a configured MCP server"],"input_types":["text"],"output_types":["structured data"],"categories":["search-retrieval","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_qustxuhao-paper-search-mcp__cap_1","uri":"capability://data.processing.analysis.paper.metadata.extraction","name":"paper metadata extraction","description":"This capability extracts structured metadata from academic papers, such as authors, publication dates, and abstracts, using a combination of OCR and NLP techniques. The integration with the MCP allows for real-time processing and retrieval of this metadata, enabling users to quickly gather essential information about papers without manual searching.","intents":["How can I extract metadata from a batch of academic papers?","What are the author details and publication dates for these papers?","Can I get abstracts for a list of papers automatically?"],"best_for":["data scientists working with academic datasets","developers building tools for literature review"],"limitations":["OCR accuracy may vary based on paper quality","Limited to supported formats for extraction"],"requires":["Python 3.8+","OCR library installed"],"input_types":["PDF","image"],"output_types":["structured data"],"categories":["data-processing-analysis","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_qustxuhao-paper-search-mcp__cap_2","uri":"capability://search.retrieval.contextual.paper.recommendations","name":"contextual paper recommendations","description":"This capability provides personalized paper recommendations based on user queries and previous interactions. By leveraging user context and preferences stored within the MCP, it generates a list of relevant papers that align with the user's research interests, improving the discovery process.","intents":["How can I get personalized recommendations for papers based on my research interests?","What papers should I read next after my last search?","Can I receive updates on new papers in my field?"],"best_for":["academics seeking to stay updated in their field","students looking for relevant literature"],"limitations":["Recommendations may not always align perfectly with user expectations","Requires user profile setup for optimal results"],"requires":["Python 3.8+","User account on the MCP server"],"input_types":["text"],"output_types":["structured data"],"categories":["search-retrieval","recommendation-systems"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":26,"verified":false,"data_access_risk":"moderate","permissions":["Python 3.8+","Access to a configured MCP server","OCR library installed","User account on the MCP server"],"failure_modes":["Performance may degrade with large datasets due to indexing overhead","Requires internet access for external paper databases","OCR accuracy may vary based on paper quality","Limited to supported formats for extraction","Recommendations may not always align perfectly with user expectations","Requires user profile setup for optimal results","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.16,"ecosystem":0.48999999999999994,"match_graph":0.25,"freshness":0.6,"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":"2026-05-24T12:16:28.136Z","last_scraped_at":"2026-05-03T15:19:49.547Z","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=qustxuhao-paper-search-mcp","compare_url":"https://unfragile.ai/compare?artifact=qustxuhao-paper-search-mcp"}},"signature":"g4CBGvbD1vZEiiJAE8XTupt6uxY2xiCKz7oei5sZghR+x4TQtXak9D/ipOIpRfYLyyl8LDb9J+3swf+SL8QyAg==","signedAt":"2026-06-23T06:45:52.540Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/qustxuhao-paper-search-mcp","artifact":"https://unfragile.ai/qustxuhao-paper-search-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=qustxuhao-paper-search-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"}}