{"uid":"cap_BULjiulFoRYzIRHJS4e6r","slug":"x402-agent-economy-lab-bulk-text-embedding-api-3fa0ddad","name":"x402 Agent Economy Lab – Bulk Text Embedding API","description":"Machine-payable NLP micro-services: sentiment, entity extraction, summarization, report, batch. Paid per call in REAL USDC on Base mainnet.","url":"https://rqjzcd-ip-209-115-177-214.tunnelmole.net/v1/embed-bulk","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"text":{"type":"string"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.02","displayCostAsset":"USDC","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":"$0.02/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_jd5sU0TIxYzherf7IIiTZ","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.02","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Generates vector embeddings for multiple texts in a single call, paid per call in real USDC on Base mainnet via the x402 payment protocol.","exampleAgentPrompt":"Embed these 10 product descriptions in bulk so I can store them in my vector database for semantic search: [list of texts].","exampleUseCases":[{"title":"RAG pipeline document ingestion","prompt":"I need to embed all 50 chunks from this document so I can load them into my Pinecone index — can you run them through the bulk embed endpoint and return the vectors?"},{"title":"Customer review clustering","prompt":"Take these 30 customer reviews and generate embeddings for all of them so I can cluster them by topic and find common themes."},{"title":"Semantic similarity for product catalog","prompt":"Vectorize these 20 product descriptions in one shot so I can compare them against user queries for a semantic search feature."}],"resultDescription":"Returns an array of dense vector embeddings, one per input text, suitable for use in semantic search, similarity comparison, clustering, or storage in a vector database.","failureModes":["Payment failure if wallet has insufficient USDC on Base mainnet — returns 402 Payment Required","Empty or missing text field returns 400 Bad Request","Oversized batch may trigger timeout or rate limiting","Tunnelmole tunnel may be offline, returning connection errors","Malformed JSON input returns 422 Unprocessable Entity"],"whenToPreferThis":"Choose this endpoint when you need to embed multiple texts in a single paid API call using the x402 micropayment protocol on Base mainnet, particularly in autonomous agent workflows that need machine-payable NLP services without traditional API key auth. Best for pipelines already integrated with x402 USDC payment rails.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T06:30:35.218Z","isFirstParty":false}