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MCP servers work best when their tools are easy for a model to choose, their results stay focused, and their configuration and outputs are handled cautiously. These four practical lessons draw on dave8172’s account of building and using MCP servers, with an important qualification: the article’s example connection flow predates the MCP specification announced on 28 July 2026.

How MCP servers fit into an AI application

Model Context Protocol (MCP) is an open standard for connecting AI applications to tools and data. In the article’s conceptual model, the host is the application running the model, the client is the connector inside that host, and the server exposes capabilities by wrapping a service or data source.

A server can make tools available for the model to select and call. The article illustrates this with an Upwork job-search integration and a JSON-RPC tools/call request. That sequence is useful as a conceptual walkthrough, not as current implementation guidance: MCP’s 2026-07-28 specification retired the previous initialize/initialized exchange and the Mcp-Session-Id header. It makes capability discovery optional through a new discovery RPC. Check the versioned specification and the relevant client SDK documentation before implementing a connection flow. Read the MCP maintainers’ announcement of the 2026-07-28 specification.

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1. Write tool descriptions that help the model choose correctly

A model choosing among tools relies on their names, descriptions, and input schemas; it does not select an operation by reading the server’s implementation code. Those descriptions and schemas are therefore part of the usable interface. Explain what a tool does, when it is appropriate, and what it returns. Give tools distinct responsibilities so similar names or overlapping descriptions do not make selection harder.

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For example, a job-search server should make clear which tool searches listings, which retrieves details, and what each expects as input. State meaningful differences in the description and schema rather than expecting the model to infer them from how the server is implemented.

The article reports a 20–25-tool “sweet spot” attributed to PagerDuty engineers, but does not provide the underlying PagerDuty source. Treat that number as an unverified attribution, not as a general limit or a measured rule. The practical test is whether the available tools are clear and distinct enough for the model to choose the right one.

2. Return the smallest result that answers the request

Tool results become part of the model’s working context. Large, unfocused responses can crowd out information that matters to the task. Return the fields and records needed to answer the request rather than a full data dump by default.

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For a job search, that could mean returning a short set of relevant listings with the fields needed to compare them, then retrieving a selected listing’s full details only when asked. This keeps the first response useful without spending context on unrelated records or data.

3. Check how local processes and credentials behave in your host

Local server lifecycle depends on the host setup

The author reports testing a local doceval MCP server in Claude Code. In that setup, the server started once per session, was reused for multiple calls, and exited when the client exited, including after a forced client termination. These are observations from that host and configuration—not a guarantee about every MCP client or deployment. Check the lifecycle behavior of the host you use, especially when relying on cleanup after an interrupted session.

Keep credentials out of committed plain-text configuration

The author also reports testing environment-variable substitution in a Claude Code configuration. Referencing a credential from the environment can avoid placing its literal value in a configuration file; use an authentication flow where suitable. A secret written directly into plain-text configuration may be exposed to processes or accidentally committed to a repository. Protect the environment or secret store that supplies the value as well.

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Local stdio and remote HTTP are different deployment choices

A local server process and a remote HTTP server have different operational and authentication considerations. The local process depends on how the host launches and stops it; a remote deployment requires its own HTTP routing and authorization setup. Choose based on where the server must run and how its credentials and access will be managed. Do not assume one host’s local process behavior describes a remote service—or another host’s behavior.

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4. Treat tool output as untrusted and review consequential actions

Tool output can include content intended to steer the model. Treat returned text as data, not as trusted instructions, and be especially careful when a tool can submit, send, publish, purchase, or otherwise change something.

The author says they personally approve each Upwork proposal and describes a preview flow. That is the author’s workflow, not evidence that every MCP client or connected service offers equivalent approval controls. For consequential actions, use a setup that lets a person inspect what will happen before it is submitted, and verify the details rather than relying on a tool result alone.

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What changed in the 2026-07-28 MCP specification

The protocol context matters because the article’s connect, initialize, discover, and call sequence reflects an older handshake model. The official announcement for the 2026-07-28 specification describes a stateless protocol core: it retires the initialize/initialized exchange and Mcp-Session-Id header, while making capability discovery optional through a new discovery RPC. It also describes Mcp-Method and Mcp-Name HTTP headers for routing, cache hints for list responses, authorization hardening, and a formal deprecation policy.

The maintainers explain the stateless design this way: “Each request is self-describing, with an optional discovery call for clients that want capabilities up front, so any request can land on any instance behind a plain round-robin load balancer.” — David Soria Parra and Den Delimarsky, MCP lead maintainers, 2026-07-28 specification announcement.

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This update is a reason to tie implementation advice to a specific specification version and client SDK. The announcement describes the protocol changes; it does not establish that every host implements them in the same way.

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