Hey everyone 👋,
If you are using AI coding agents (Cursor, Claude, Copilot) on large codebases, you probably face two massive problems:
Token Exhaustion: Sending your entire workspace into the context window drains your API budget instantly.
LLM Hallucinations: When AI gets overwhelmed with thousands of lines of irrelevant implementation logic, it loses focus, hallucinates, and breaks your architectural boundaries.
To solve this, I built and open-sourced T-Zero Context Architect V3.
How it crushes hallucinations & token costs: T-Zero doesn't just blindly read files. It uses an AST-based static analyzer to strip out all the "fat" (long function implementations) while keeping the absolute "skeleton" (class/method signatures, docstrings, decorators, and imports).
This allows you to map your entire enterprise-grade project into the LLM's context window, reducing token usage by up to 95% while maintaining 100% semantic fidelity. The AI sees exactly how your app works without getting distracted by the inner logic of irrelevant functions.
🤖 Native MCP Server Embedded: T-Zero V3 natively embeds a Model Context Protocol (MCP) server. By simply adding a 1-line JSON config to Cursor, Claude Desktop, or Antigravity IDE, you give your AI agent access to 13 autonomous tools.
Before writing a single line of code, your AI can now autonomously:
Generate a T-Zero context tree of your workspace.
Query cross-module dependency graphs.
Audit for "Code Smells" and duplicities.
Enforce strict "Zero-Leak" architecture boundaries.
🔒 100% Zero-Leak Security: It uses OS-level keyring encryption. No API keys are ever stored in plain text. It also fully supports local LLMs (like Ollama) for a $0 cost, 100% offline dry-run context generation.
I would love for the community to test it, try breaking it, and tell me what you think. It's completely free and MIT-licensed.
🔗 GitHub Repo: https://github.com/toprakahmetaydogmus/TZeroAlgorithm
Feedback and PRs are highly appreciated! Let's cure LLM hallucinations together. 💻✨
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