Verleihen Sie Ihrem KI-Assistenten ein tiefes Verständnis jeder Codebasis
Ein eigenständiger MCP-Server, der Code-Analysedaten für Gemini, Claude, Cursor, Windsurf, VS Code Copilot bereitstellt — mit persistentem KI-Gedächtnis zwischen Konversationen.
Your Code → CodeAtlas Analyze → MCP Server → AI Understands Everything
│
10 powerful tools:
• Search functions & classes
• Trace feature flows
• Generate architecture diagrams
• Persistent memory across conversationsVor CodeAtlas: Die KI durchsucht den Code blind und vergisst Ihr Projekt bei jeder neuen Konversation. Nach CodeAtlas: Die KI kennt sofort Ihre Architektur, Abhängigkeiten und behält den Kontext bei.
Related MCP server: code-intel MCP Server
Installieren Sie die CodeAtlas-Erweiterung und führen Sie dann Folgendes aus:
Ctrl+Shift+P → CodeAtlas: Analyze Project{
"mcpServers": {
"codeatlas": {
"command": "npx",
"args": ["-y", "@giauphan/codeatlas-mcp"]
}
}
}{
"mcpServers": {
"codeatlas": {
"command": "npx",
"args": ["-y", "@giauphan/codeatlas-mcp"]
}
}
}{
"mcp": {
"servers": {
"codeatlas": {
"command": "npx",
"args": ["-y", "@giauphan/codeatlas-mcp"]
}
}
}
}{
"mcpServers": {
"codeatlas": {
"command": "npx",
"args": ["-y", "@giauphan/codeatlas-mcp"]
}
}
}claude mcp add codeatlas -- npx -y @giauphan/codeatlas-mcp{
"mcpServers": {
"codeatlas": {
"command": "npx",
"args": ["-y", "@giauphan/codeatlas-mcp"]
}
}
}Fertig! Ihre KI kann nun alle 10 CodeAtlas-Tools verwenden.
Tool | Beschreibung | Anwendungsbeispiel |
| Alle analysierten Projekte auflisten | "Welche Projekte habe ich?" |
| Module, Klassen, Funktionen abrufen | "Zeige mir alle Klassen" |
| Import-/Aufruf-/Enthaltungsbeziehungen | "Wovon hängt UserService ab?" |
| Code-Qualitäts- & Sicherheitsanalyse | "Gibt es Sicherheitsprobleme?" |
| Entitäten per Fuzzy-Suche finden | "Finde die Login-Funktion" |
| Alle Entitäten in einer bestimmten Datei | "Was ist in auth.ts enthalten?" |
Tool | Beschreibung | Anwendungsbeispiel |
| Mermaid-Architekturdiagramm (Modulimporte) | "Zeige mir die Systemarchitektur" |
| Mermaid-Ausführungsflussdiagramm (Aufrufketten) | "Wie funktioniert die Zahlungsfunktion?" |
Tool | Beschreibung | Anwendungsbeispiel |
| Kontext in | "Merke dir, was wir geändert haben" |
| Feature durch die Codebasis verfolgen | "Welche Dateien sind an der Authentifizierung beteiligt?" |
KI-Assistenten vergessen alles zwischen Konversationen. CodeAtlas behebt dies:
Conversation 1 → AI analyzes code → sync_system_memory
│
.agents/memory/
├── system-map.md ← Architecture diagram
├── modules.json ← All entities
├── conventions.md ← Code patterns
├── business-rules.json ← Domain logic
├── feature-flows.json ← Feature traces
└── change-log.json ← Change history
│
Conversation 2 → AI reads memory → full context restored instantly ✨Wenn Sie Analyze Project ausführen, erstellt CodeAtlas automatisch Regeldateien für Ihre KI-IDE:
Generierte Datei | Für |
| Alle KI-Assistenten |
| Cursor |
| Claude Code |
| Windsurf |
Diese weisen Ihre KI an:
Zu Beginn jeder Konversation .agents/memory/ zu lesen
MCP-Tools zu verwenden, bevor Änderungen vorgenommen werden
sync_system_memory nach Abschluss von Änderungen aufzurufen
Sprache | Funktionen |
TypeScript / JavaScript | Vollständiger AST: Importe, Klassen, Funktionen, Variablen, Aufrufe, Implementierungen |
Python | Klassen, Funktionen, Variablen, Importe, Aufrufe |
PHP | Klassen, Interfaces, Traits, Enums, Funktionen, Eigenschaften |
Blade Templates |
|
npm install -g @giauphan/codeatlas-mcpVerwenden Sie dann "command": "codeatlas-mcp" in Ihrer MCP-Konfiguration (keine args erforderlich).
Variable | Beschreibung |
| Erzwingt ein bestimmtes Projektverzeichnis |
Standardmäßig erkennt der Server automatisch alle Projekte mit
.codeatlas/analysis.jsonunter~/.
git clone https://github.com/giauphan/codeatlas-mcp.git
cd codeatlas-mcp
npm install
npm run build
npm test # 6 tests
npm start # Start MCP serverCodeAtlas-Erweiterung — VS Code-Erweiterung mit interaktivem Code-Graphen
MCP-Protokoll — Standard für das Model Context Protocol
MIT — Kostenlos für den persönlichen und kommerziellen Gebrauch.
Generate a Mermaid diagram showing the EXECUTION FLOW of a feature. Unlike generate_system_flow (which shows module imports), this traces the actual call chain: entry point → controller → service → model → database. Given a keyword, it finds all related functions and classes, then builds a flowchart or sequence diagram showing how they call each other at runtime. This is the best tool for understanding HOW a feature works step-by-step.
Inputs: keyword (required), project, diagramType, depth, +1 more.
Auto-generate a Mermaid flowchart diagram showing how modules, classes, and functions connect in the system. Returns a Mermaid diagram string that AI can read to understand the full system flow without reading every file.
Inputs: project, scope, feature, maxNodes.
Get import/call/containment/implements relationships between entities. Shows how modules, classes, and functions are connected.
Inputs: project, source, target, relationship, +1 more.
Get all entities (classes, functions, variables) defined in a specific file.
Inputs: filePath (required), project.
Get AI-generated code insights including refactoring suggestions, security issues, and maintainability analysis.
Inputs: no named parameters.
Get all modules, classes, functions, and variables in the analyzed project. Returns entity type, name, file path, and line number.
Inputs: project, type, limit.
List all projects that have been analyzed by CodeAtlas. Returns project names, paths, and last analysis time.
Inputs: no named parameters.
Search for functions, classes, modules, or variables by name. Supports fuzzy matching.
Inputs: query (required), project, type.
Create or update the .agents/memory/ folder with auto-generated system documentation. This folder serves as AI's 'long-term memory' — it persists between conversations. After calling this, AI in any future conversation can read these files to understand the full system flow without re-analyzing. Call this after completing any code changes.
Inputs: project, businessRule, changeDescription.
Trace the complete flow of a feature through the codebase. Given a keyword (e.g. 'login', 'payment', 'crawl'), finds all related files, classes, and functions, then orders them by dependency chain to show the execution flow. This helps AI understand which files to read when working on a feature.
Inputs: keyword (required), project, depth.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
Scored across 10 tools
Most tools have distinct purposes. However, `generate_feature_flow_diagram` and `trace_feature_flow` both trace feature flow by keyword, differing only in output format (diagram vs. ordered list). Descriptions help differentiate, but an agent might still select the wrong one for a given need.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., `generate_feature_flow_diagram`, `get_dependencies`, `list_projects`). No mixed conventions or vague verbs.
With 10 tools, the set covers the domain of code analysis and documentation well. Each tool serves a distinct, necessary function without redundancy or bloat.
The tool surface covers core CRUD-like operations for projects and entities, plus advanced analysis (flows, insights, memory sync). Minor gaps exist, such as no tool for editing entities or comparing versions, but core workflows are supported.
Search indexed code, trace dependencies, assess change impact, and recall repository memory.
The Cortex MCP server provides read-only access to real-time engineering context from the Cortex developer portal, allowing AI coding assistants to answer natural language questions about your organization's catalog (microservices, libraries, domains, teams, infrastructure), scorecards (engineering standards and best practices), initiatives (goals and deadlines), and Engineering Intelligence metrics. It includes tools for querying documentation, tracking personal entities, and accessing AI-assisted insights across the entire Cortex ecosystem.
Give your AI agent a persistent map of your project's structure, dependencies, and bugs.
Code intelligence for LLMs. Analyze, search, and retrieve code from any public git repository.
