The Biomimetic Context Engine & Neural Runtime for AI Coding Assistants
How does nature pack two metres of DNA into a nucleus without deleting a single letter? Not by throwing genes away — by folding.
NeuroMesh does the same thing to your repository: a neural graph in RAM, reversible one-line folds, and an evidence packet instead of three thousand-line files dumped into Cursor or Claude.
Local-first MCP · Cursor · Codex · OpenCode · MiMo CLI · Antigravity · VS Code · Claude · Kilo · Trae · Windsurf · Zed
The pain · The idea · Galaxy · Install · Connect · Docs · Site
You ask a simple question in a large project. The editor copies two or three thousand-line files and ships them to the model.
1. Tokens you never needed — dollar cost on every turn 2. Seconds of fake loading while the window fills with helpers you will not touch 3. Lost in the middle — the model drowns in unrelated bodies and invents bugs
Today’s workarounds all leak in a different place:
Approach What goes wrong :--- :--- Vector RAG Chunks smash functions. The shape of the code disappears. “Just attach the files” The model sees everything and understands nothing. A static code graph Better map — then it still pastes full files into the prompt.
NeuroMesh is the missing step: route first, then fold. The graph is for finding the path. The packet is what the model actually reads.
Nature does not delete DNA to fit a nucleus. It supercoils.
NeuroMesh treats the syntax tree like a genetic strand in RAM:
From the project README.
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