# AgentTools Text Chunker

> AgentTools Text Chunker is a paid API for AI agents from agenttools-hub.vercel.app, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-02).

Splits a block of text into sentence-aware, token-budgeted chunks with configurable overlap for RAG pipeline preparation

## Facts

- Endpoint: GET https://agenttools-hub.vercel.app/api/v1/dev/text-chunker?utm_source=zero.xyz
- Price: $0.002/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/agenttools-text-chunker-cb284d80
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ASTFCtrVlbKmtUnv7Gofh

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 agenttools-text-chunker-cb284d80
```

Example prompt: Can you chunk this article into segments of about 256 tokens each with a 32-token overlap so I can embed them for RAG? Here's the text: [paste text here]

## When to prefer this

Choose this endpoint when you need sentence-aware, token-budgeted chunking with configurable overlap as a preprocessing step before embedding text into a vector store or RAG pipeline. It is ideal when you need deterministic, reproducible splits with context preservation across chunk boundaries, and you do not want to implement chunking logic yourself.

## Known failure modes

- Missing required 'text' query parameter returns an error
- Non-numeric values for targetTokens or overlapTokens may cause parsing errors
- Extremely short text may result in a single chunk regardless of token budget
- Very large text inputs may hit request size limits
- Overlap larger than targetTokens may cause undefined or degenerate chunking behavior

## How this service works

Split text into retrieval-friendly chunks with a token budget and sentence-aware boundaries. Overlap between consecutive chunks preserves context across splits — the standard preparation step before embedding. Use this when an agent needs to rAG-ready chunks with token budgets and overlap.

## Output

Returns an array of text chunks, each respecting sentence boundaries and fitting within the specified token budget, with consecutive chunks sharing an overlapping window of tokens to preserve context across splits.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method"
   ],
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "GET"
     ],
     "type": "string"
    },
    "queryParams": {
     "type": "object",
     "required": [
      "text"
     ],
     "properties": {
      "text": {
       "type": "string",
       "description": "Text"
      },
      "targetTokens": {
       "type": "number",
       "description": "Target tokens per chunk"
      },
      "overlapTokens": {
       "type": "number",
       "description": "Overlap tokens"
      }
     }
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object"
    }
   }
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/agenttools-text-chunker-cb284d80/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from agenttools-hub.vercel.app](https://www.zero.xyz/host/agenttools-hub.vercel.app/llms.txt)