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ContextSlim MCP API – Fetch Cached Context (GET)
x402
ContextSlim MCP API – Fetch Cached Context (GET) is a paid API for AI agents from contextslim.friczero.com, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-15).
Retrieves a previously optimized and cached context payload using a reference ID returned by the optimize_context tool.
Price / call$0.001
Success—
StatusUnknown
How this service works
[MCP: optimize_context] Pay-per-call JSON context pruning & LLM token budget enforcement. Saves up to 85% prompt tokens.
Output
Returns the pruned JSON payload previously generated by optimize_context, along with token metrics (original tokens, slimmed tokens, tokens saved, reduction percentage, strategy applied) and a tool result reference object containing the referenceId, fetchTool name, and expiry duration. Delivered as a JSON object with a 'success' status field.
Example use cases
Multi-turn agent memory retrieval
“I ran a context optimization earlier that returned reference ID 'ref_abc99'. Fetch that cached slim payload now so the agent can pick up where it left off without re-sending the full JSON.”
Low-latency tool result reuse
“Retrieve the ContextSlim cached result for reference 'ref_xyz456' — I need the pruned tool output back quickly to feed into the next step of my pipeline without re-processing.”
Long-running workflow checkpoint
“My agent stored a compressed context snapshot with ID 'ref_turn7_session3'. Get that back for me so we can resume the workflow from that checkpoint instead of starting fresh.”
Technical details
Endpoint
GEThttps://contextslim.friczero.com/messageWhen to prefer
Use this endpoint when an agent has already called optimize_context and received a referenceId, and now needs to retrieve the cached pruned payload — especially across conversation turns or pipeline steps. Prefer this over re-running optimization when the cached result is still within its TTL, to save tokens and cost. Ideal for multi-turn LLM agents and long-running workflows where re-transmitting full JSON is prohibitive.
Side effects
- Missing or invalid referenceId returns an error — the referenceId query parameter is required and must be non-empty
- Expired referenceId (past 3600s TTL) returns a cache miss or not-found error
- Invalid or malformed MCP method enum value causes a schema validation error
- Payment failure or missing x402 header results in a 402 Payment Required response
- Network timeout or upstream KV cache unavailability causes a 5xx error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"result": {},
"status": "success",
"metrics": {
"savedTokens": 528,
"slimmedTokens": 94,
"originalTokens": 622,
"strategyApplied": "prune_arrays",
"reductionPercentage": "84.9%"
},
"toolResultReference": {
"expiresIn": "3600s",
"fetchTool": "fetch_result",
"referenceId": "ref_12345678"
}
}
}Tags
x402
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