{"uid":"cap_z43o94ijd0lntjJWh7SpP","slug":"llms-generator-agentdiet-dev-arxiv-ai-cs-paper-search-structured-46976e8e","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://llms-generator.agentdiet.dev/v1/llm-benchmark-papers)","url":"https://llms-generator.agentdiet.dev/v1/llm-benchmark-papers?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_8xidBCHS-n9zpviMQ43Js","protocol":"mpp","methodType":"crypto","chain":"tempo","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fcd6edb6e08f4c7c32d4f71b54bda02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":"llms-generator.agentdiet.dev","brandSlug":"llms-generator-agentdiet-dev-mpp","brandBaseUrl":"https://llms-generator.agentdiet.dev","brandDocsUrl":null,"whatItDoes":"Searches ArXiv for AI, CS, and math papers by topic or paper ID, returning 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 for LLM benchmarking","prompt":"Search ArXiv for papers on LLM benchmark evaluation and give me structured abstracts, author lists, and BibTeX citations so I can build my literature review."},{"title":"Fetch specific preprint by ID","prompt":"Pull up ArXiv paper 2308.11432 for me — I need the full abstract, authors, PDF link, and a BibTeX entry I can drop into my references."},{"title":"Track diffusion model research","prompt":"Find the latest ArXiv papers on diffusion models for image generation and return their abstracts and PDF links so I can scan what's new this month."}],"resultDescription":"Returns structured records for matching ArXiv papers, including title, abstract, author list, PDF download link, and BibTeX-formatted citation entry, packaged in a token-efficient digest format.","failureModes":["Invalid or non-existent ArXiv paper ID returns no results or an error","Overly broad query returns low-relevance papers","ArXiv API rate limiting may cause delayed or failed responses","Payment via x402/USDC required; missing or failed payment results in HTTP 402 response","Very narrow or misspelled topic queries may return empty results"],"whenToPreferThis":"Choose this endpoint when an agent needs to retrieve structured academic paper metadata from ArXiv — especially abstracts, BibTeX citations, and PDF links — in a token-efficient format. Prefer it over raw ArXiv API calls when you need pre-digested, agent-ready output. It is especially useful when you have either a specific ArXiv paper ID or a topic query and need actionable citation data without parsing raw XML.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T07:22:57.117Z","isFirstParty":false,"canonicalSlug":"llms-generator-agentdiet-dev-arxiv-ai-cs-paper-search-structured-d1b5bffa"}