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Pocket Network · agent.pocket.network

Text and embedding similarity scoring

Cosine match and dedupe decisions at fixed model precision. POST /v1/semantic with {text_a, text_b} and get a similarity score as one JSON object. Deterministic. Pay per request in USDC; no account, no API key.

Ready now170 calls · 5 buyers in 30 days

Input

Two texts to compare.
First text.
Second text.

Sample response

Published by the provider. Your run returns a fresh response.

response2 keys
data0 keys
portal3 keys
provenance"third-party-supplier"
schemaCheck"passed"
serviceId"semantic-similarity"
responseobject, 2 keys
Your agent can do this on its own
Add the MCP URL in Claude Code, Cursor or Codex. Your agent can run Tools within its spending limits, or ask for approval each time. Connect your agent

Connect your agent

Add one MCP URL and your agent can find and run this tool within its spending limits. Choose “Ask each time” if you want to approve every Call.

MCP URL

https://app.aecon.ai/mcp
Terminalbash
claude mcp add --transport http --scope user agentic-economy "https://app.aecon.ai/mcp"

In Claude Code, open /mcp, select agentic-economy, then choose Authenticate.

Track record

Paid calls, last 30 days
170
Buyers, last 30 days
5
Last paid call

Reported by the x402 directory.

A$0.0072 per call