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mcp-rubber-duck

Verified Safe

by nesquikm

Overview

An MCP server acting as a bridge to query and orchestrate multiple OpenAI-compatible LLMs for rubber duck debugging and multi-agent operations.

Installation

Run Command
npx mcp-rubber-duck

Environment Variables

  • OPENAI_API_KEY
  • GEMINI_API_KEY
  • GROQ_API_KEY
  • TOGETHER_API_KEY
  • PERPLEXITY_API_KEY
  • ANYSCALE_API_KEY
  • AZURE_OPENAI_API_KEY
  • AZURE_OPENAI_ENDPOINT
  • OLLAMA_BASE_URL
  • CUSTOM_{NAME}_API_KEY
  • CUSTOM_{NAME}_BASE_URL
  • DEFAULT_PROVIDER
  • DEFAULT_TEMPERATURE
  • LOG_LEVEL
  • MCP_SERVER
  • MCP_BRIDGE_ENABLED
  • MCP_APPROVAL_MODE
  • MCP_APPROVAL_TIMEOUT
  • MCP_TRUSTED_TOOLS
  • MCP_TRUSTED_TOOLS_{SERVER_NAME}
  • MCP_SERVER_{NAME}_TYPE
  • MCP_SERVER_{NAME}_URL
  • MCP_SERVER_{NAME}_COMMAND
  • MCP_SERVER_{NAME}_ARGS
  • MCP_SERVER_{NAME}_API_KEY

Security Notes

The server employs robust security measures, including extensive use of environment variables for secrets, a `SafeLogger` to redact sensitive data, and `JSON.parse` for LLM outputs which safely handles malformed JSON without code execution. The `FunctionBridge` facilitates calls to external MCP servers, including `stdio` commands which are configured by the operator, not dynamically generated from user input. Argument validation using `Ajv` and an `ApprovalService` (configurable for 'always', 'trusted', or 'never' modes, with session-based memory) provide strong defenses against malicious tool calls, requiring human intervention for untrusted actions. The overall architecture is designed with security in mind for its intended use case, with the primary remaining risk lying in potential misconfiguration of `stdio` commands by the operator.

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Stats

Interest Score70
Security Score9
Cost ClassHigh
Avg Tokens1000
Stars115
Forks18
Last Update2025-12-08

Tags

mcpllmopenai-compatiblemulti-agentdebugging