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MCP Server Template

by stevennevins
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TypeScript
Hybrid

MCP 服务器模板

先决条件

LLM CLI 安装

该项目需要安装 LLM CLI。您可以使用 Homebrew 安装它：

brew install llm

安装后，通过运行以下命令确保llm命令在您的 PATH 中可用：

llm --version

Related MCP server: MCP Server Template

入门

发展

  1. 安装依赖项：

    npm install

  2. 使用热重载启动开发服务器：

    npm run dev

  3. 构建项目：

    npm run build

  4. 运行测试：

    npm test

  5. 启动生产服务器：

    npm start

建筑师工具

Architect 工具 ( src/tools/architect.ts ) 提供了一个与 LLM CLI 交互的接口，用于获取架构设计反馈。它维护对话上下文并处理应用程序与 LLM CLI 之间的通信。

特征

  • 在多次互动中保持对话上下文

  • 通过 LLM CLI 处理命令执行

  • 提供错误处理和日志记录

  • 支持新对话和持续讨论

要求

  • 必须安装 LLM CLI 并在您的 PATH 中可用（请参阅先决条件部分）

  • 应为 LLM CLI 正确配置环境变量

测试

该模板包括用于本地测试的内置 TestClient 和用于可视化调试的 MCP Inspector。

使用 TestClient

TestClient 提供了一种测试工具的简单方法：

import { TestClient } from "./utils/TestClient";

describe("YourTool", () => {
  const client = new TestClient();

  it("should process data correctly", async () => {
    await client.assertToolCall(
      "your-tool-name",
      { input: "test" },
      (result) => {
        expect(result.toolResult.content).toBeDefined();
      }
    );
  });
});

使用 MCP 检查器

该模板包括用于工具可视化调试的 MCP 检查器：

  1. 启动检查器：

    npx @modelcontextprotocol/inspector node dist/index.js

  2. 在http://localhost:5173打开检查器 UI

检查员提供：

  • 测试工具的可视化界面

  • 实时请求/响应监控

  • 工具元数据检查

  • 交互式测试环境

使用游标进行本地测试

要使用 Cursor 在本地测试您的 MCP 服务器：

  1. 构建并链接包：

    npm run build
npm run link

  2. 验证二进制文件是否有效：

    npx architect-test-mcp-tool

  3. 将服务器添加到 Cursor：

    • 打开光标设置

    • 导航至“功能”选项卡

    • 向下滚动到 MCP 服务器部分

    • 点击“添加服务器”

    • 选择“命令”类型

    • 给它起一个名字（例如，“本地示例工具”）

    • 输入命令： npx architect-test-mcp-tool

    • 点击确认

  4. 通过检查 MCP 服务器部分是否显示您的服务器正在运行，验证服务器是否在 Cursor 中正确启动。

注意：如果您更改了代码，请记住重建并重新链接：

npm run build
npm run link

完成测试后，您可以取消链接包：

npm run unlink

这将删除在开发期间创建的全局符号链接。

故障排除

使用 MCP 检查器

MCP 检查器是一款实用的工具，可用于调试和检查您的 MCP 服务器。使用方法如下：

  1. 首先，构建你的项目：

    npm run build

  2. 运行检查器：

    npx @modelcontextprotocol/inspector node dist/index.js

检查器提供了一个 Web 界面，允许您：

  • 查看所有可用工具及其方案

  • 测试工具交互调用

  • 检查请求/响应有效载荷

  • 调试服务器和客户端之间的通信问题

Available Tools

1 tool
architectC

MCP server for the LLM Architect tool. Exposes resource "/llm-architect/chat" accepting POST requests with a prompt and optional conversationId, and interacts with the llm chat CLI to provide architectural design feedback while maintaining conversation context.

ParametersJSON Schema
NameRequiredDescriptionDefault
conversationIdNoOptional conversation ID for context
inputYesInput prompt to process

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool 'interacts with the llm chat CLI to provide architectural design feedback while maintaining conversation context,' which implies it's a read/write operation with state persistence. However, it lacks details on authentication needs, rate limits, error handling, or what specific 'architectural design feedback' entails. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, starting with the tool's role as an MCP server and its key functionality. It uses two sentences efficiently: the first covers the resource and parameters, and the second explains the interaction with the CLI and purpose. There's minimal waste, though it could be slightly more concise by integrating the two ideas more tightly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (a chat-based tool with conversation context), no annotations, and no output schema, the description is moderately complete. It explains the tool's purpose and parameters but lacks details on behavioral traits like response format, error cases, or specific feedback mechanisms. For a tool without structured output information, it should do more to compensate, but it provides a basic viable understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds some semantic context beyond the input schema. It mentions that the tool accepts 'a prompt and optional conversationId,' which aligns with the schema's 'input' (required) and 'conversationId' (optional) parameters. However, with 100% schema description coverage (both parameters have descriptions in the schema), the description doesn't provide additional meaning or usage examples. This meets the baseline of 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: it's an MCP server that exposes a resource for POST requests to interact with an LLM chat CLI for architectural design feedback. It specifies the verb ('interacts with'), resource ('/llm-architect/chat'), and context ('maintaining conversation context'). However, since there are no sibling tools mentioned, it doesn't need to distinguish from alternatives, so it falls just short of a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides minimal usage guidance. It mentions that the tool accepts POST requests with a prompt and optional conversationId, but it doesn't explain when to use this tool versus other potential tools (though none are listed as siblings), nor does it provide context about when this specific architectural feedback tool is appropriate versus general chat tools. No exclusions or alternatives are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedarchitect
Deploy Server
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

TDQS

B3/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'architect' has a clearly defined and distinct purpose, so an agent cannot misselect between non-existent alternatives.

Naming Consistency5/5

A single tool inherently exhibits perfect naming consistency, as there are no other tools to compare against. The name 'architect' follows a simple, readable pattern without any conflicting conventions.

Tool Count2/5

One tool is too few for a server named 'MCP Server Template', which implies a broader or more general-purpose scope. A template server should ideally offer multiple tools to demonstrate a range of capabilities, making this count inappropriate for the apparent purpose.

Completeness1/5

The server is severely incomplete for its implied domain as a template. It only provides a single chat interaction tool, lacking any CRUD operations, configuration tools, or other functionalities expected from a template that should showcase a comprehensive tool surface for agents to learn from.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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