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Context Optimization Methods

HasMCP exclusively uses two interceptor engines designed to slice, prune, and transform heavy JSON payloads received from external provider APIs before they impact the final LLM Context Window:

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1. JMESPath Pruning

JMESPath is a declarative query language built for slicing JSON natively. It serves as a rapid structural filter mechanism.
  • Ideal For: Extracting subsets of matrices (data.results[].{id: object_id, value: metadata}), filtering specific nodes, isolating exact strings nested in heavy arrays.
  • Benefit: Very fast execution. Safe declarative syntax preventing infinite loops.

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2. Goja (JavaScript) Interceptors

Goja is a pure functional JavaScript execution engine built to parse deeply complex or logical data transformations securely at the proxy edge.
  • Ideal For: Math operations (summing array values), dynamic redaction rules (detecting regex string boundaries), parsing complex non-standard encodings (base64).
  • Benefit: Absolute programmatic freedom to reconstruct the exact JSON object your specific Agent expects organically.
[!IMPORTANT] Execution Timeouts: Both GoJA and JMESPath interceptors enforce a strict 100ms execution timeout on HasMCP Cloud versions to ensure real-time proxy speed and prevent infinite loops. Enterprise on-prem versions allow administrators to define their own custom timeout values depending on their infrastructure capabilities.