{"uid":"cap_8j0Tp_i3qd4AMkOrjRTWq","slug":"company-enrich-agentdiet-dev-arxiv-ai-cs-paper-search-structured-da0176ad","name":"ArXiv AI/CS Paper Search & Structured Token-Diet Digest","description":"Queries ArXiv for AI/CS/math papers and returns structured abstracts, authors, PDF links, and BibTeX. (Live x402 v2, IETF MPP & MCP endpoint at https://company-enrich.agentdiet.dev/v1/paper-summary)","url":"https://company-enrich.agentdiet.dev/v1/paper-summary?utm_source=zero.xyz","method":"GET","headers":{},"bodySchema":{"type":"object","required":["query"],"properties":{"query":{"type":"string","minLength":1,"description":"ArXiv paper ID (e.g. 2308.11432) or research topic search query"}}},"responseSchema":{"type":"object"},"example":null,"exampleRequest":null,"tags":[],"displayCostAmount":"0.01","displayCostAsset":"USD","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"mpp","network":"tempo","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"mpp","network":"tempo","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_MVWL2_S7_c3SE7xVhQRKr","protocol":"mpp","methodType":"crypto","chain":"tempo","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fcd6edb6e08f4c7c32d4f71b54bda02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":"company-enrich.agentdiet.dev","brandSlug":"company-enrich-agentdiet-dev-mpp","brandBaseUrl":"https://company-enrich.agentdiet.dev","brandDocsUrl":null,"whatItDoes":"Searches ArXiv for AI, CS, or math papers by topic or paper ID and returns structured abstracts, authors, PDF links, and BibTeX citations.","exampleAgentPrompt":"Can you search ArXiv for recent papers on chain-of-thought prompting and give me the abstracts, authors, PDF links, and BibTeX for the top results?","exampleUseCases":[{"title":"Literature review on a research topic","prompt":"Search ArXiv for the most relevant papers on diffusion-based image generation models and give me the structured abstracts, author lists, and BibTeX so I can build a literature review."},{"title":"Fetch metadata for a specific preprint","prompt":"I have this ArXiv paper ID — 2305.10601 — can you pull the full abstract, authors, PDF link, and BibTeX citation for it?"},{"title":"Keeping up with AI safety research","prompt":"Find me recent ArXiv papers on AI alignment and RLHF, and return the structured summaries and PDF links so I can read through them this week."}],"resultDescription":"Returns a structured object containing the paper title, abstract, list of authors, publication date, ArXiv URL, direct PDF link, and BibTeX citation string for each matching paper. When queried by paper ID, returns a single paper's full metadata; when queried by topic, returns a list of relevant matching papers.","failureModes":["Invalid or non-existent ArXiv paper ID returns no results or an error","Overly broad or ambiguous topic queries may return loosely relevant papers","ArXiv API rate limiting may cause timeouts or delayed responses","Very niche or recent papers may not yet be indexed","Empty query string is rejected due to minLength:1 validation"],"whenToPreferThis":"Choose this endpoint when you need structured, machine-readable metadata (abstract, authors, BibTeX, PDF link) for ArXiv papers — either by known paper ID or by topic search — particularly in agentic workflows that need citation-ready output without scraping ArXiv HTML. Prefer over raw ArXiv API access when you need pre-digested, token-efficient structured output ready for downstream use.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T12:51:18.350Z","isFirstParty":false,"canonicalSlug":"company-enrich-agentdiet-dev-arxiv-ai-cs-paper-search-structured-da0176ad"}