I built T-Zero V3, an open-source MCP Server that cures LLM hallucinations and cuts token context costs by up to 95% 🚀

A developer has released T-Zero Context Architect V3, an open-source tool that uses AST-based static analysis to strip function implementations from a codebase while preserving signatures, docstrings, decorators and imports, claiming token reductions of up to 95% for AI coding agents. The release embeds a native Model Context Protocol (MCP) server exposing 13 autonomous tools for context-tree generation, dependency-graph queries, code-smell audits and architecture-boundary enforcement, and is MIT-licensed with OS-level keyring encryption and support for local LLMs such as Ollama.

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 https://github.com/toprakahmetaydogmus/TZeroAlgorithm Feedback and PRs are highly appreciated Let's cure LLM hallucinations together. 💻✨