# AgentUtility Semantic Chunk

> AgentUtility Semantic Chunk is a paid API for AI agents from x402.agentutility.ai, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-14).

Splits a block of text into overlapping semantic chunks using configurable chunk size, overlap, and chunking mode (e.g. sentence)

## Facts

- Endpoint: POST https://x402.agentutility.ai/semantic-chunk
- Price: $0.005/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/agentutility-semantic-chunk-03cb6387
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8uunTjmnwc-7j7QdHgn9C

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability agentutility-semantic-chunk-03cb6387 -d '<json body>'
```

Example prompt: Can you split this article text into sentence-mode chunks of size 300 characters with an overlap of 50 characters so I can embed them for a RAG pipeline? Here's the text: 'Artificial intelligence is reshaping industries worldwide. Companies are investing heavily in machine learning. The results are transformative across healthcare, finance, and logistics.'

## When to prefer this

Choose this endpoint when you need lightweight, local (no third-party LLM) text chunking with configurable overlap and sentence-aware splitting for RAG ingestion, embedding preparation, or document preprocessing — especially when you want deterministic, reproducible chunks at low cost ($0.005 per call) without sending data to a large AI model.

## Known failure modes

- Missing or empty text input returns an error or empty chunk array
- chunk_size smaller than a single sentence may produce degenerate chunks
- overlap larger than chunk_size may cause infinite loops or errors
- Non-string text input may cause a 400 validation error
- Payment not attached or insufficient USDC causes x402 payment-required response

## How this service works

Paid x402 endpoints organized into product clusters. USDC-settled on Base. MCP-callable. ERC-8004 identity registry agentId 47167.

## Output

Returns a JSON object containing the chunking mode used, chunk size, overlap, total character count, number of chunks, and an array of chunk objects each with start offset, end offset, character count, and the chunk text string.

## Request schema (JSON Schema)

```json
{
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "type": "object",
 "properties": {
  "input": {
   "type": "object",
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "type": "string",
     "enum": [
      "POST"
     ]
    },
    "bodyType": {
     "type": "string",
     "enum": [
      "json",
      "form-data",
      "text"
     ]
    },
    "body": {
     "properties": {
      "text": {
       "type": "string",
       "description": "Text to split. Up to 1,000,000 chars."
      },
      "chunk_size": {
       "type": "number",
       "description": "Target chunk size in characters. Range [50, 20000]. Default 500."
      },
      "overlap": {
       "type": "number",
       "description": "Overlap between chunks in characters. Default 50. Capped at chunk_size - 1."
      },
      "mode": {
       "type": "string",
       "enum": [
        "fixed",
        "sentence",
        "paragraph"
       ],
       "description": "Splitting strategy. Default 'fixed'."
      }
     },
     "required": [
      "text"
     ]
    }
   },
   "required": [
    "type",
    "method",
    "bodyType",
    "body"
   ],
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object",
     "properties": {
      "chunks": {
       "type": "array",
       "items": {
        "type": "object",
        "properties": {
         "text": {
          "type": "string"
         },
         "start": {
          "type": "integer"
         },
         "end": {
          "type": "integer"
         },
         "char_count": {
          "type": "integer"
         }
        }
       }
      },
      "chunk_count": {
       "type": "integer"
      },
      "mode": {
       "type": "string"
      },
      "chunk_size": {
       "type": "integer"
      },
      "overlap": {
       "type": "integer"
      },
      "text_chars": {
       "type": "integer"
      },
      "source": {
       "type": "string"
      }
     }
    }
   },
   "required": [
    "type"
   ]
  }
 },
 "required": [
  "input"
 ]
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "mode": "sentence",
  "chunks": [
   {
    "end": 33,
    "text": "First sentence. Second sentence. ",
    "start": 0,
    "char_count": 33
   },
   {
    "end": 52,
    "text": "Second sentence. Third one. Fourth.",
    "start": 17,
    "char_count": 35
   }
  ],
  "source": "DIY (pure local)",
  "overlap": 10,
  "chunk_size": 30,
  "text_chars": 52,
  "chunk_count": 2
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/agentutility-semantic-chunk-03cb6387/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from x402.agentutility.ai](https://www.zero.xyz/host/x402.agentutility.ai/llms.txt)