codeatlas-platform

mcp
Guvenlik Denetimi
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SUMMARY

AI-powered codebase intelligence platform — MCP Server, AST analysis, Knowledge Graph, and semantic memory with SQLite + sqlite-vec. Analyze any codebase in minutes.

README.md

CodeAtlas Platform

CI
Node.js
License: MIT
npm version
GitHub release

AI-powered codebase intelligence platform — MCP Server, AST analysis, Knowledge Graph, and semantic memory with SQLite + sqlite-vec as the default database.

Ship a secure, multi-tenant codebase intelligence backend without rebuilding authentication, MCP tooling, semantic memory, and knowledge graph infrastructure from scratch. CodeAtlas Platform is an open-source foundation for developers who want a clear starting point for AI-native code analysis services.

[!IMPORTANT]
This repository is a foundation, not a substitute for a threat model. Review Known limitations and adapt the defaults to your infrastructure before serving production traffic.

Why this platform?

Concern Included foundation
MCP Server 30+ tools via stdio or SSE transport (Claude, Cursor, VSCode)
Semantic memory Dream memory store with SQLite + sqlite-vec vector search
Knowledge graph Genome DNA + immune system patterns, consolidation engine
Multi-tenant Tenant isolation via authStorage.run + Firebase auth
AST analysis TypeScript/Python/JS parsing via @typescript-eslint/typescript-estree and py-ast
Security scanner Enterprise vulnerability scanning built-in
A2A protocol Agent-to-agent orchestration with registry
Dashboard React + Vite management UI for API keys and projects

Architecture

AI IDE (Claude/Cursor) → MCP (stdio/SSE) → Platform :3381 → SQLite + sqlite-vec + Firebase + NVIDIA
Layer Components
Presentation Express HTTP, MCP SSE, A2A Agent Protocol, REST API
Services Dream Memory, Genome DNA, Second Brain, Consolidation Engine, Security Scanner
Data SQLite + sqlite-vec (PostgreSQL optional), Firebase Firestore, NVIDIA NIM embeddings

Architecture diagrams

Diagram File
System architecture diagrams/system.mmd
Second Brain flow diagrams/second-brain.mmd
Dream lifecycle diagrams/dreams.mmd
Genome + Immune system diagrams/genome.mmd
MCP architecture architecture/mcp.md
Deployment diagrams/deployment.mmd
A2A + Sync diagrams/a2a-sync.mmd

Quick start

Requirements

  • Node.js 20+
  • pnpm 9+ (corepack enable && corepack prepare pnpm@9 --activate)
  • SQLite + sqlite-vec (bundled — no external database server required)
  • Firebase service account (for multi-tenant auth)
  • NVIDIA NIM API key (for embeddings)

1. Clone and install

git clone https://github.com/giauphan/codeatlas-platform.git
cd codeatlas-platform
pnpm install

2. Configure environment

cp .env.example .env
# Edit .env with your Firebase and NVIDIA credentials

See docs/CONFIGURATION.md or docs/DEVELOPMENT.md for the full env var reference.

3. Build

pnpm run build

4. Initialize database

pnpm run db-init

5. Start the server

# Production mode (SSE on :3381)
PORT=3381 pnpm start

# Development mode (hot reload)
pnpm run dev

# Stdio mode (for Claude Desktop — leave PORT unset)
pnpm start

Server runs at http://localhost:3381. Health check: GET /health.

MCP integration

Claude Desktop (stdio)

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "codeatlas": {
      "command": "npx",
      "args": ["-y", "codeatlas-ai"],
      "env": {
        "CODEATLAS_API_KEY": "your_api_key"
      }
    }
  }
}

Cursor / VSCode (SSE)

{
  "mcpServers": {
    "codeatlas": {
      "url": "http://localhost:3381/sse"
    }
  }
}

See docs/API_EXAMPLES.md for full curl flows and transport modes.

MCP tools (30+)

Category Tools
Dreams save_dream_memory, query_dream_memories, sync_dreams
Genome search_genome, save_genome, scan_immune
Skills search_skills, get_skill, install_skill
Scanner scan_enterprise_vulnerabilities
Code code_search, search_files, read_file
Projects list_projects, get_project_structure, get_dependencies
Architecture generate_system_flow, generate_feature_flow_diagram, trace_feature_flow

Full tool reference: docs/architecture/mcp.md.

Documentation

Guide Purpose
Development Local dev setup, env vars, troubleshooting
Deployment PM2, systemd, Nginx TLS reverse proxy
API examples curl flows, MCP configs, REST endpoints
Architecture overview Layers, services, integrations
MCP architecture Tool registration, transports, request flow
Quick setup Legacy condensed guide

Known limitations

  • SQLite dependency: Data lives in a local SQLite file (default ./data/codeatlas.db) with sqlite-vec for vector search. Postgres is available as an opt-in backend.
  • Firebase auth: Multi-tenant mode requires Firebase Admin SDK + service account. API-key-only mode supported for single-tenant.
  • NVIDIA embeddings: Vector search depends on NVIDIA NIM API. Without NVIDIA_API_KEY, queries fall back to date-ordered results.
  • Local indexing: Pure cloud deployments cannot index local code — run the codeatlas-ai client locally to sync AST data.
  • Dashboard: Management UI ships separately in dashboard/ — build and deploy independently.

See CHANGELOG.md for release history.

Contributing

Bug reports, documentation fixes, tests, and focused feature contributions are welcome. Start with CONTRIBUTING.md, then look for issues labeled good first issue or help wanted.

For security vulnerabilities, follow SECURITY.md instead of opening a public issue.

License

Distributed under the MIT License. Maintained by @giauphan.

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