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New tool drastically cuts AI coding agent token use with codebase graph

A new open-source tool called codebase-memory-mcp has been released to optimize AI coding agents by creating a persistent knowledge graph of codebases. This tool significantly reduces token usage by allowing agents to query structural information directly, rather than performing extensive file searches. Benchmarks show a 99% reduction in token consumption for typical queries, freeing up more tokens for the agent to focus on problem-solving and improving session speed and cost-efficiency. AI

IMPACT Reduces token costs and improves efficiency for AI coding agents by enabling direct structural queries.

RANK_REASON New open-source tool release for AI coding agents.

Read on dev.to — MCP tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New tool drastically cuts AI coding agent token use with codebase graph

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  1. dev.to — MCP tag TIER_1 English(EN) · ArshTechPro ·

    Stop Making Your AI Coding Agent Grep Your Whole Repo — Try codebase-memory-mcp

    <p>If you use an AI coding agent — Claude Code, Codex CLI, Gemini CLI, Cursor, Zed, Aider, whatever — you've probably watched it burn through tens of thousands of tokens just trying to figure out who calls a function or where a route is defined. It greps, it reads files, it greps…