Keep the tool result, its source, and its timestamp distinguishable from the model’s interpretation.
Understand the role of a tool
A question about the latest gold quote needs an observation from a data source. Our recommended AI workflow retrieves that observation first, then lets the model explain it. A fluent answer alone is not evidence that a fresh request succeeded.
The MCP tools specification defines named tools with descriptions and input schemas. Clients discover tools through tools/list and invoke them through tools/call. Tool results can include structured content, giving the application something more precise to inspect than an unstructured paragraph. [1]
Keep the request small and explicit
For a gold data workflow, we suggest a small set of focused operations: retrieve a quote, request candles for a specified interval, or inspect feed status. Require the parameters that change the meaning of the result, and validate them on the server.
Return the source, symbol, price basis, and observation time with the values. In the final answer, distinguish the retrieved measurement from any explanation derived from it. If the request fails or the observation is too old for the question, say that fresh data is unavailable rather than substituting a remembered price.
Keep access outside the prompt
Configure credentials through the client’s supported authentication mechanism rather than placing secrets in chat messages. The server must verify access on each protected operation; a model’s statement that the user is authorized cannot replace that check.
MCP’s security guidance prohibits token passthrough: a server must not blindly accept and forward tokens intended for another service. When building a bridge, follow the intended authentication flow and audience checks. Treat the upstream data-provider credential as a separate secret with its own access boundary. [2]
Verify behavior, not just labels
The tools specification says clients must treat tool annotations as untrusted unless they come from trusted servers. A read-only label is useful metadata, but it is not a substitute for understanding and restricting the tool’s actual capabilities. [1]
Test the answer end to end
Our suggested test set includes a successful quote, stale data, a denied request, and a tool error. Check that the answer preserves units and timestamps, reports missing data accurately, and does not reveal credentials. Keep retrieved text as data rather than allowing it to override the application’s instructions.
Finally, separate data retrieval from actions such as placing orders. A workflow designed to explain market observations should not acquire trading permissions merely because an assistant can call tools. Grant only the capabilities the product actually needs.
References
Primary sources for the technical details in this article. Implementation suggestions are our own.