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AgentTools Text Chunker
x402
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
Price / call$0.002
Success—
StatusUnknown
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.
Example use cases
RAG pipeline document preparation
“I have a long research paper I want to embed into my vector database — can you split it into 512-token chunks with 64 tokens of overlap so each chunk stays sentence-aware?”
Chunking FAQ for chatbot knowledge base
“Take this FAQ document and break it into retrieval-friendly chunks of 200 tokens with a 20-token overlap so my chatbot can find the right answer snippets.”
Preprocessing news articles for semantic search
“I need to chunk this news article into 128-token pieces with 16 tokens of overlap before I embed it — can you do that and give me all the chunks?”
Technical details
Endpoint
GEThttps://agenttools-hub.vercel.app/api/v1/dev/text-chunker?utm_source=zero.xyzWhen to prefer
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.
Side effects
- 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
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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