Agent as MCP Client: The Standard Interaction Pattern
The foundational MCP interaction: an AI agent connects to MCP servers and calls their tools to take governed action in enterprise systems.
The Standard Interaction Pattern
Agent as MCP Client is the foundational interaction pattern: an AI agent connects to one or more MCP servers and calls their tools to take action in enterprise systems. The agent is the decision-maker; the MCP server is the governed action executor.
The flow is: agent receives a goal, agent reasons about which tools to call, agent calls tool via MCP protocol, tool executes against the enterprise system, tool returns structured result, agent reasons about the result and decides next action.
Tool Selection and Context
The agent selects which tool to call based on the tool's name and description. This is why the design principles matter: if tool descriptions are accurate and specific, the agent selects the right tool reliably. If descriptions are vague or technically oriented, the agent guesses — and guesses wrong.
In Workato's implementation, the agent also receives context about which tools are available at initialization. Large tool sets (50+) can saturate the context window. Follow the 10–25 tool guideline per server, and use the Orchestration-Federated pattern to curate the tool set when multiple servers are involved.
Error Handling in the Client Pattern
When an MCP tool call fails, the agent must decide what to do next. Does it retry? Does it try a different tool? Does it escalate to a human? This behavior must be designed — the agent's default behavior when a tool fails is to reason based on the error response. If the error response is unstructured ("500 Internal Server Error"), the agent has nothing useful to reason with. Return structured error responses from every tool.