MCP-Nexus
Verified Safeby Gustavocoello
Overview
An intelligent conversational AI assistant designed to enhance developer productivity by providing free, local generative AI capabilities and integrating with external services via the Model Context Protocol.
Installation
python backend/app.pyEnvironment Variables
- OPEN_ROUTER_0
- OPEN_ROUTER_1
- OPEN_ROUTER_2
- OPEN_ROUTER_3
- OPEN_ROUTER_4
- OPEN_ROUTER_5
- AZURE_VISION_ENDPOINT
- AZURE_KEY1
- CLERK_JWKS_URL
- CLERK_DOMAIN
- CLERK_SECRET_KEY
- GOOGLE_CLIENT_ID
- GOOGLE_CLIENT_SECRET
- GOOGLE_CLIENT_SECRET_JSON
- REDIS_URL
- SECRET_KEY
- FERNET_SECRET_KEY
- ROOT_BD
- USER_BD
- PASS_BD
- NAME_BD
- USER_BD_AZURE
- PASS_BD_AZURE
- NAME_BD_AZURE
- ROOT_BD_AZURE
- ONEDRIVE_REDIRECT_URI
- ONEDRIVE_SCOPES
- ONEDRIVE_AUTHORITY
- AZURE_CLIENT_ID
- AZURE_CLIENT_SECRET
- AZURE_TENANT_ID
- FRONTEND_URL
- BACKEND_URL
- MCP_SECRET_KEY
- MCP
- USUARIO_TEST
- ENV
- TEST_MODE
- INIT_KEEP_ALIVE
- VITE_CLERK_PUBLISHABLE_KEY
- VITE_URL
- VITE_DEBUG
- VITE_MCP_URL
Security Notes
The project employs strong security practices including JWT-based authentication via Clerk, OAuth 2.0 for Google and OneDrive integrations, and Fernet encryption for sensitive tokens stored in the database. API keys and database credentials are properly managed through environment variables. File uploads are processed with text extraction and rate-limited for Azure AI Vision, reducing abuse potential. CORS is explicitly configured with a list of allowed origins, mitigating common web vulnerabilities. No obvious direct 'eval' of user input or malicious code patterns were identified. Potential risks could stem from the security of third-party libraries used for file parsing (e.g., pypdf, docx2txt) or the secure configuration of numerous external APIs.
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