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AgentDiet Context Window Distiller
x402
AgentDiet Context Window Distiller is a paid API for AI agents from status.agentdiet.dev, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-22).
Compresses and distills AI agent context windows, reducing token usage by up to 85-91% for A2A/MCP workflows, paid via USDC on Base.
Price / call$0.001
Success—
StatusUnknown
How this service works
Deterministic B2A/A2A/MCP/x402/MPP/L402 execution and intelligence node at https://status.agentdiet.dev settling in USDC on Base.
Output
Returns a JSON object with a status field ('ok'), a data object containing the distilled/compressed output, and a roi_proof object showing the compression_ratio_pct (e.g. 91.4%). This lets the caller verify token savings quantitatively.
Example use cases
Agent pipeline token cost reduction
“My multi-agent pipeline is burning through tokens because context keeps growing — can you run the current context through AgentDiet to strip the bloat and tell me what compression ratio we achieved?”
MCP node context slimming
“Before passing context to the next MCP node, distill it with AgentDiet in GET mode so we stay under the context limit and I can see proof of how much we compressed.”
LLM inference cost audit
“Use AgentDiet to compress the context at this URL and give me the ROI proof showing the compression percentage so I can justify the token savings to my team.”
Technical details
Endpoint
GEThttps://status.agentdiet.dev/v1?utm_source=zero.xyzWhen to prefer
Choose AgentDiet when you need deterministic, metered context compression for A2A or MCP agent pipelines and want cryptographic ROI proof of token savings. Prefer this over generic summarization when you need consistent compression ratios, micropayment-gated access via x402/USDC, and integration with B2A/MCP/L402 protocols rather than a one-off summarization API.
Side effects
- Invalid or unreachable URL in query params returns error status
- Payment not settled in USDC on Base causes 402 rejection
- Unsupported HTTP method (not GET or POST) returns schema validation error
- Context content too large or malformed may yield empty or partial data
- Missing required 'input' object with type and method causes request rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"data": {},
"status": "ok",
"roi_proof": {
"compression_ratio_pct": 91.4
}
}
}Tags
x402
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