Chat-Based MCP Orchestration Agent
Chat-driven AI agent that interprets user intent and routes requests either to internal reasoning or to external tools via an MCP client.
This workflow implements a chat-based AI agent that acts as a central decision and orchestration layer. Each incoming chat message is passed to the agent, which evaluates the user’s intent based on a predefined system prompt.
Depending on the request, the agent either responds directly using its internal reasoning or delegates execution to external systems through an MCP (Model Context Protocol) client. The MCP client serves as a controlled bridge to tools such as calendars, email, spreadsheets, vector databases, or other external services.
A chat model is used for language understanding and intent interpretation, while a lightweight memory component retains short-term conversational context to maintain continuity across interactions. The separation between reasoning, memory, and tool execution keeps the workflow predictable and easier to extend.
This setup focuses on controlled tool usage, explicit decision-making, and clear boundaries between the agent and external execution layers.
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