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Merge pull request #22 from rushikeshmore/v0.5.0-knowledge-layer
fix: revert to knowledge layer positioning, add cold-start framing
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CLAUDE.md

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# CodeCortex
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Codebase navigation and risk layer for AI agents. Pre-builds a map of architecture, dependencies, coupling, and risk areas so agents go straight to the right files.
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Persistent codebase knowledge layer for AI agents. Pre-builds architecture, dependency, coupling, and risk knowledge so agents skip the cold start and go straight to the right files.
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## Stack
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- TypeScript, ESM (`"type": "module"`)

README.md

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# CodeCortex
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Codebase navigation and risk layer for AI agents. Pre-builds a map of architecture, dependencies, coupling, and risk areas so agents go straight to the right files.
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Persistent codebase knowledge layer for AI agents. Pre-builds architecture, dependencies, coupling, and risk knowledge so agents skip the cold start and go straight to the right files.
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[![CI](https://github.com/rushikeshmore/CodeCortex/actions/workflows/ci.yml/badge.svg)](https://github.com/rushikeshmore/CodeCortex/actions/workflows/ci.yml)
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[![npm version](https://img.shields.io/npm/v/codecortex-ai)](https://www.npmjs.com/package/codecortex-ai)
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## The Solution
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CodeCortex gives agents a pre-built map: architecture, dependencies, risk areas, hidden coupling. The agent goes straight to the right files and starts working.
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CodeCortex eliminates the cold start. It pre-builds codebase knowledge — architecture, dependencies, risk areas, hidden coupling — so agents skip the exploration phase and go straight to the right files.
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**CodeCortex finds WHERE to look. Your agent still reads the code.**
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**Not a middleware. Not a proxy. Just knowledge your agent loads on day one.**
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Tested on a real 6,400-file codebase (143K symbols, 96 modules):
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package.json

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{
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"name": "codecortex-ai",
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"version": "0.5.0",
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"description": "Codebase navigation and risk layer for AI agents — architecture, dependencies, coupling, and risk areas served via MCP",
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"description": "Persistent codebase knowledge layer for AI agents — architecture, dependencies, coupling, and risk served via MCP",
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"type": "module",
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"bin": {
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"codecortex": "dist/cli/index.js"

src/mcp/server.ts

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* CodeCortex MCP Server
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*
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* Serves codebase knowledge to AI agents via Model Context Protocol.
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* 13 tools: 10 read (navigation + risk) + 3 write (knowledge creation).
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* 13 tools: 8 read + 5 write (navigation, risk, memory).
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*
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* Usage:
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* codecortex serve
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const server = new McpServer({
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name: 'codecortex',
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version: '0.5.0',
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description: 'Codebase navigation and risk layer for AI agents. Pre-built map of architecture, dependencies, coupling, and risk areas.',
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description: 'Persistent codebase knowledge layer for AI agents. Architecture, dependencies, coupling, risk, and cross-session memory.',
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})
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registerReadTools(server, projectRoot)

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