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NewsMaterial3 min readDisconfirmAI Editorial

AWS Developer Advocate James Ward: MCP Servers Should Be the Third Voice in Conversations, Driving Tool Iteration with Guidance and Session Tracing

James Ward of AWS believes that when MCP servers return data, they should carry next-step guidance and stitch together complete call paths via session IDs, enabling teams to observe agent behavior, identify tool defects, and validate improvements through evaluations.

2026-10-29 23:55 GMT+8

At the AGNTCon + MCPCon conference, James Ward, a senior developer advocate at AWS, put forward a core argument regarding MCP server design: the protocol's best use is not for servers to act as databases, but to serve as a third voice in the conversation. He envisions a scenario where, when you have multiple MCP servers, they each play the role of a fourth or fifth participant in the dialogue, rather than merely being queried data sources.

The specific mechanism Ward proposes is this: tool responses should not only return data but also carry guidance—telling the agent what it just did, what it might want to do next, and where to find more information. This means MCP servers transform from passive query interfaces into active participants; their output itself becomes the input for the agent's next step in reasoning.

Observability is the other half of this proposition. Ward points out that while web developers can trace a single page click all the way down to the database, MCP has no default trace ID mechanism. AWS's solution is quite straightforward: add a session ID parameter to tools and require agents to pass it with every call, thereby stitching scattered calls into a complete path. A second parameter can carry the user's original prompt or a summary of their goal. Teams can then compare what the user wanted with the path the agent actually took, build evaluations around this path, adjust tool descriptions or parameters, and measure whether task completion rates improve.

A concrete example illustrates the value of this approach. In a profile piece published by the Agentic AI Foundation, Ward described a scenario where an agent fetched customer records one by one because the server only provided a single-record query tool. It was by observing the complete call path that the team spotted this pattern and subsequently built a batch tool to fix it. Without end-to-end visibility, such inefficient calls could remain hidden beneath the surface of seemingly normal operations for a long time.

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Ward does not present MCP as the sole solution. He acknowledges that AWS also offers CLIs and skills interfaces, partly because MCP's OAuth model cannot switch between AWS user profiles the way a CLI can. Which method works best depends on the model, tool descriptions, and how the agent discovers tools, so AWS compares them side-by-side using evaluations. He also admits that this methodology is not novel—observing paths, reproducing issues, measuring improvements, and iterating on tools are old principles of software engineering; the new requirement is simply to understand the path taken jointly by humans and agents, and to verify whether changes to tools truly help complete tasks.

Notably, this article was sponsored by AWS Marketplace, and Ward himself is an AWS employee; the practices described are those used by internal AWS developers for their MCP servers. This is an engineering proposition from a vendor perspective, not the result of independent third-party verification. The session ID scheme relies on agents cooperating to pass parameters; it is not a mandatory constraint at the protocol level. Whether it can be promoted across the broader MCP ecosystem depends on whether various implementations are willing to accept this convention.

Sources

  • thenewstack.ioThe New Stack↗
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