mcp-rubber-duck
Verified Safeby nesquikm
Overview
An MCP (Model Context Protocol) server that acts as a bridge to query multiple OpenAI-compatible LLMs, enabling multi-agent AI workflows and providing an AI 'rubber duck' debugging panel.
Installation
npx mcp-rubber-duckEnvironment Variables
- MCP_SERVER
- OPENAI_API_KEY
- DEFAULT_PROVIDER
- MCP_BRIDGE_ENABLED
- GUARDRAILS_ENABLED
- GUARDRAILS_PII_REDACTOR_ENABLED
Security Notes
The server demonstrates a strong commitment to security through several features: a robust MCP tool approval service with 'always', 'trusted', and 'never' modes, session-based approvals, and per-server trusted tool lists. It incorporates a pluggable 'Guardrails' system for runtime safety, including Rate Limiting, Token Limiting, Pattern Blocking, and PII Redaction. Sensitive data is actively sanitized from logs using `SafeLogger`. Input validation is performed for external tool calls via AJV. Global error handlers (`uncaughtException`, `unhandledRejection`) are in place for crash diagnosis and stability. API keys are managed via environment variables or config files, avoiding hardcoding in the codebase. Network calls to external LLMs and MCP servers are inherent to its bridging function but are managed within these security layers. The project structure and practices suggest a high degree of security awareness for its intended use case.
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