langgraph-dev-navigator
by botingw
Overview
Provides a RAG and Knowledge Graph powered backend for grounding AI coding assistants in the LangGraph ecosystem, improving code generation accuracy and reducing hallucinations.
Installation
docker run -i --rm --memory "512m" -v "$(pwd)/mcp-crawl4ai-rag/.env:/app/.env" mcp-crawl4ai-rag bash /app/start_mcp_server.shEnvironment Variables
- DATABASE_URL
- NODE_ENV
- FRONTEND_URL
- ADMIN_PASSWORD
- OPENAI_API_KEY
- GOOGLE_API_KEY
- ANTHROPIC_API_KEY
- DEEPSEEK_API_KEY
- AZURE_OPENAI_API_KEY
- SILICONFLOW_API_KEY
- AZURE_OPENAI_MODEL_DEPLOYMENT
- NEO4J_URI
- NEO4J_USER
- NEO4J_PASSWORD
- SUPABASE_URL
- SUPABASE_SERVICE_KEY
- TRANSPORT
- USE_KNOWLEDGE_GRAPH
- USE_AGENTIC_RAG
- USE_HYBRID_SEARCH
- USE_RERANKING
- TAVILY_API_KEY
- SERPAPI_API_KEY
Security Notes
Critical: Admin authentication uses direct plaintext password comparison (from environment variable) with no rate limiting, vulnerable to brute-force attacks. Database SSL (`rejectUnauthorized: false`) is insecure in production, risking Man-in-the-Middle (MITM) attacks. High Risk: Python tools (`llm_api.py` for LLM interaction, `web_scraper.py` for web scraping) expose potential local file exfiltration (via image encoding or generic file read prompts) and arbitrary URL fetching if AI agents are maliciously prompted. Minor: Content Security Policy (CSP) and Cross-Origin Embedder Policy are disabled in development mode for the Express API, requiring hardening for production. Logging of environment variable keys at startup in `llm_api.py` is a minor information leak.
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