pluggedin-app
Verified Safeby VeriTeknik
Overview
A testing environment for MCP (Model Control Protocol) servers, allowing interaction through a chat interface powered by LLMs and an AI agent using the LangChain ReAct framework.
Installation
docker run -p 3000:3000 veriteknik/pluggedin:latestEnvironment Variables
- DATABASE_URL
- REDIS_URL
- NEXTAUTH_URL
- NEXTAUTH_SECRET
- PLUGGEDIN_API_KEY
- MCP_ISOLATION_TYPE
- MCP_ISOLATION_FALLBACK
- MCP_ENABLE_NETWORK_ISOLATION
- MCP_PACKAGE_STORE_DIR
- MCP_PNPM_STORE_DIR
- MCP_UV_CACHE_DIR
- REGISTRY_API_URL
- ANTHROPIC_API_KEY
- OPENAI_API_KEY
- GOOGLE_API_KEY
- EMAIL_SERVER_HOST
- EMAIL_SERVER_PORT
- EMAIL_SERVER_USER
- EMAIL_SERVER_PASSWORD
- EMAIL_FROM
- EMAIL_FROM_NAME
- EMAIL_REPLY_TO
- UPLOADS_DIR
- NEXT_SERVER_ACTIONS_ENCRYPTION_KEY
- RAG_API_URL
- UNSUBSCRIBE_TOKEN_SECRET
- ADMIN_NOTIFICATION_EMAILS
- GITHUB_CLIENT_ID
- GITHUB_CLIENT_SECRET
- GOOGLE_CLIENT_ID
- GOOGLE_CLIENT_SECRET
- TWITTER_CLIENT_ID
- TWITTER_CLIENT_SECRET
- GITHUB_TOKEN
- ALLOWED_REDIRECT_HOSTS
- METRICS_ALLOWED_IPS
- CRON_SECRET
Security Notes
The application exhibits a robust security posture, incorporating numerous defense-in-depth measures. Key strengths include: comprehensive input validation and sanitization (URLs, paths, external IDs, HTML content) to prevent XSS, path traversal, and SSRF attacks; strong authentication security with bcrypt (cost factor 14), brute-force protection (account lockout), and detailed audit logging; secure session management with JWTs, periodic revalidation, and session invalidation on password changes; robust data encryption (AES-256-GCM with scrypt and random salts) for sensitive data at rest; global CSRF protection and HTTP security headers (CSP with nonce, X-Frame-Options, X-Content-Type-Options, etc.); and critical sandboxing capabilities for executing external MCP server code via Bubblewrap/Firejail for process, filesystem, and network isolation. While in-memory rate limiting is noted as a 'CRITICAL TODO' for multi-instance deployments in one file, other files show the use of `ioredis` for distributed rate limiting, mitigating this, though fallback to in-memory still presents a risk if Redis fails. `process.setMaxListeners` is used, which is a practical mitigation but could be a resource exhaustion vector if many STDIO servers are connected concurrently without proper scaling.
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