pal-mcp-server-multi-model-orchestration

Multi-model orchestration coordinates Gemini, OpenAI, Anthropic, Grok, Azure, Ollama, and OpenRouter in one continuous flow for consensus-driven code review, debugging, and security validation. It preserves a shared conversation thread so later models build on earlier analysis.

Running isolated CLI subagents requires using the clink bridging feature, which executes specialized CLI subagents in isolated contexts for heavy tasks. This isolation prevents workspace contamination while performing deep security auditing or pre-commit checks.

Yes, multi-model orchestration supports Ollama alongside OpenRouter and other providers for security auditing. You can route local models through parameters like prompt, model, conversation_id, and max_tokens to validate code changes locally.

Configuring an MCP server for pre-commit checks requires setting up the pal tool with provider API keys and model routing. You define clink subagent roles and use parameters like prompt and max_tokens to execute multi-model audits on code changes.

Consensus-based multi-model audits solve the problem of inconsistent code review quality by leveraging different AI model strengths. Orchestrating multiple providers together ensures comprehensive planning, debugging, and security validation that a single model might miss.