Hermes Micro-Agent — Extract

x402

Hermes Micro-Agent — Extract is a paid API for AI agents from hermesmicroservice.theworkpc.com, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-30).

Extracts structured information or key details from a given text using a paid AI micro-task over HTTP 402 (USDC on Base)

Price / call$0.1

Seller volume →—

Success—

StatusUnknown

How this service works

20 paid AI and data micro-tasks over HTTP 402 on Base (USDC): summarize, extract, keywords, sentiment, translate, rewrite, proofread, python_debug, code_lint, code_explain, code_refactor, code_review, json_minify, json_query, csv_to_json, hash, base64, convert, describe_image, probe_media. Each call is priced per-task and verified on-chain before execution.

Output

Returns a plain-text string containing the extracted information or entities as identified by the AI from the provided input text.

Example use cases

Extract entities from contract text

“Pull out all the parties involved, dates, and monetary values from this contract clause: 'Effective January 1, 2025, GlobalTech Inc. agrees to pay Horizon Solutions $120,000 annually, renewable each year through December 31, 2027.'”

Extract action items from meeting notes

“Extract every action item and the person responsible from these meeting notes: 'Sarah will finalize the Q3 budget by Friday. Tom needs to send the updated proposal to the client before Thursday. Dev team to complete code review by end of week.'”

Pull product specs from a description

“Extract the product name, dimensions, weight, and price from this listing: 'The UltraSlim X200 laptop measures 13.3 inches, weighs 2.8 lbs, has a 512GB SSD and 16GB RAM, and retails for $1,299.'”

Technical details

Endpoint

POSThttps://hermesmicroservice.theworkpc.com/extract?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need a lightweight, pay-per-use AI extraction task without provisioning a full NLP pipeline. It is ideal for agents that occasionally need to pull structured information from text on demand, especially in crypto-native workflows where USDC micropayments on Base are already in use. Prefer it over heavier ML services when cost predictability ($0.10/call) and simplicity matter more than fine-tuned domain-specific accuracy.

Side effects

Missing required 'prompt' field returns an error
Ambiguous extraction target may produce incomplete or inaccurate results
Payment failure (402 not settled on-chain) blocks task execution
Very long input text may be truncated or produce partial extractions
Malformed JSON in request body returns a 400-level error

Input

Schema · Request body

Field	Type	Description
task	string	Which micro-task to run
input	string	Alias for prompt
promptrequired	string	Text to process

Output

Schema · Response

{
  "type": "string"
}

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