IA-QA — 152 QA & Dev Tools for AI Agents

embedding_similarity

Read-onlyIdempotent

Compute text similarity using local algorithms (Bag of Words, TF-IDF, Character N-grams). No API key needed — runs entirely in-process. NOT real embeddings: true vector embeddings are run_semantic_tests with mode="embeddings" and an OpenAI key. Supports single pair or batch mode with pipe-separated pairs. Useful for RAG retrieval testing, semantic search evaluation, and text deduplication.

Input Schema

Name	Required	Description
`batch`	No	Batch mode: array of { text_a, text_b } pairs. Overrides text_a/text_b if provided.
`text_a`	No	First text to compare (single-pair mode)
`text_b`	No	Second text to compare (single-pair mode)
`methods`	No	Algorithms to use (default: all three). Options: "bow", "tfidf", "ngram"

Output Schema

Name	Required	Description	Default
`mode`	No
`count`	No
`scores`	No
`text_a`	No
`text_b`	No
`results`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 31, 2026

addedInput schema / examples

Added value: +[
+  {
+    "text_a": "the cat sat",
+    "text_b": "quantum field theory"
+  }
+]

Changed1 schema field changedJun 21, 2026

addedOutput schema / properties

Added value: +{
+  "count": {
+    "type": "number"
+  },
+  "mode": {
+    "type": "string"
+  },
+  "results": {},
+  "scores": {},
+  "text_a": {},
+  "text_b": {}
+}

Changed1 schema field changedJun 10, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "type": "object"
+}

First observedMay 26, 2026

TDQS

Score is being calculated.

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