Name: embedding-similarity
Price: 0.002 USDC
Availability: InStock

$ man embedding-similarity

agentutility / wordmint / embedding-similarity

PRICE / CALL

$0.002

USDC · base mainnet · scheme: exact

METHOD

POST

CLUSTER

wordmint

CATEGORY

uncategorized

STATUS

● live

NAME

embedding-similarity — embedding similarity / cosine similarity / semantic match / vector compare / are-these-strings-similar

SYNOPSIS

POST https://x402.agentutility.ai/embedding-similarity
     Content-Type: application/json
     X-PAYMENT:    <signed-transferWithAuthorization>

     { ... }

↳ first call → 402 Payment Required. Sign USDCtransferWithAuthorization, retry with theX-PAYMENT header.

DESCRIPTION

Embedding similarity / cosine similarity / semantic match / vector compare / are-these-strings-similar. Embeds two strings via Venice (default model: text-embedding-bge-m3) and returns the cosine similarity as a single float in [-1, 1]. Useful for paraphrase detection, dedup, and cheap retrieval routing.

INPUT — request schema

property	type	description	req?
text_a	string	First text. Up to 30,000 chars.	required
text_b	string	Second text. Up to 30,000 chars.	required
model	string	Venice embedding model. Default 'text-embedding-bge-m3'.	optional

OUTPUT — response shape

field	type	description
text_a	string	Echoes back the first input string that was embedded for comparison.
text_b	string	Echoes back the second input string that was embedded for comparison.
similarity	string	Cosine similarity between the two embeddings as a float in [-1, 1]; 1 means identical direction.
model	string	Venice embedding model used to produce the vectors, defaults to text-embedding-bge-m3.
dimensions	string	Number of dimensions in each embedding vector returned by the model.
source	string	Upstream embedding provider that generated the vectors, typically venice.

EXAMPLES — two ways to call

EXAMPLE 1 · curl

curl -X POST https://x402.agentutility.ai/embedding-similarity \
  -H 'Content-Type: application/json' \
  -d '{ }'

first response = 402 Payment Required with payment requirements; sign + retry with X-PAYMENT.

EXAMPLE 2 · mcp

# MCP packages on npm under
# @agentutility/mcp-*  (one per cluster)
#
# Catalog + install:
# https://mcp.agentutility.ai
#
# Or call embedding-similarity directly over HTTP — see above.

MCP server handles payment automatically — your coding agent just calls the tool by name.

METADATA

tags: wordmintembeddingscosine-similaritysemantic-searchvector-compareparaphrase-detectiondedupembedding-similarity
methods: POST
cluster: wordmint
price: $0.002 USDC per call

ADJACENT — other endpoints in wordmint

endpoint	description	price
cron-explain	Cron expression explainer / cron parser / scheduling translator.	$0.002
cron-parse	Cron parser.	$0.002
dictionary-define	English dictionary / word definition / lookup word / pronunciation / part of speech / synonyms / etymology adjacent.	$0.002
regex-test	Regex tester / pattern matcher / regex playground / verify-a-pattern / match-and-capture extractor.	$0.002
semantic-chunk	Semantic chunker / text splitter / RAG chunker / chunking with overlap / sentence + paragraph aware.	$0.002
text-embedding	Text embedding / vector embedding / semantic vector / Venice embeddings / Gemini embeddings / BGE-M3.	$0.002
thesaurus	Thesaurus / synonyms / antonyms / similar words / rhymes / Datamuse / paraphrasing / query expansion.	$0.002
content-simhash	SimHash / 64-bit content fingerprint / near-duplicate detection / dedup hashing / locality-sensitive hash.	$0.001