trace-mcp

AI agents recompute the same work. trace-mcp makes them reuse instead. The recomputation → reuse layer for AI systems.

40–50% fewer tokens on average  ·  up to 2× effective capacity  ·  up to 99% less redundant processing

Based on early benchmarks across agent workflows with repeated context and dependency traversal.

AI systems don't scale because they recompute instead of reuse. Every turn, the agent re-reads the same files, re-traverses the same dependencies, and re-inflates the context window with structure it already discovered. Token bills grow. Latency grows. Reasoning quality drops. The model isn't the bottleneck — the recomputation leak is. trace-mcp builds a framework-aware graph of your codebase once, then serves it through MCP so the agent reasons from a precomputed structure instead of brute-r…