Skip to main content
Glama
enesjakozh
MatthewDailey

MCP Starter Server

by MatthewDailey
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

MCP 入门服务器

用于构建 AI 助手工具的极简ModelContextProtocol服务器模板。此入门模板提供了创建可与 Claude 等 AI 助手配合使用的 MCP 工具的基本结构。

特征

  • 简单的“hello world”工具示例

  • TypeScript + esbuild 设置

  • 预配置的开发工具

Related MCP server: MCP Server Scaffold

设置以使用 Claude 进行构建和运行

  1. 从claude.ai/download下载并安装 Claude 桌面应用程序

  2. 克隆 repo、安装依赖项并构建：

npm install
npm run build

  1. 配置 Claude 使用此 MCP 服务器。如果这是您的第一个 MCP 服务器，请在项目的根目录中运行：

echo '{
  "mcpServers": {
    "mcp-starter": {
      "command": "node",
      "args": ["'$PWD'/dist/index.cjs"]
    }
  }
}' > ~/Library/Application\ Support/Claude/claude_desktop_config.json

这应该会导致您的claude_desktop_config.json中出现如下条目：

"mcpServers": {
  "mcp-starter": {
    "command": "node",
    "args": ["/Users/matt/code/mcp-starter/dist/index.cjs"]
  }
}

如果您已有 MCP 服务器，请将mcp-starter块添加到现有配置中。需要注意的是， args是<path_to_repo_on_your_machine>/mcp-starter/dist/index.cjs的路径。

  1. 重新启动 Claude Desktop。

  2. 在 Claude 的界面中查找带有可用工具数量的锤子图标，以确认服务器正在运行。

  3. 如果一切顺利，您应该能够使用npm run dev开发您的 MCP 服务器，并在 Claude 中测试它。每次重启 Claude 时，您都需要重启 MCP 服务器。

使用 Inspector 进行开发

您可以使用 MCP Inspector 工具进行开发和调试。该工具提供了一个可视化界面，用于测试和监控 MCP 服务器的交互。

请访问Inspector 文档以获取详细的设置说明。

使用 Inspector 进行本地测试：

npm run inspect

要基于文件更改进行构建，请运行：

npm run watch

或者同时运行观察者和检查者：

npm run dev

出版

一旦您准备好分发服务器，一切都很简单！

  1. 设置NPM帐户。

  2. 运行npm publish 。这将使用package.json中的项目名称发布一个包

  3. 一旦发布，其他人就可以使用如下配置条目安装服务器：

"mcpServers": {
  "<your-package-name>": {
    "command": "npx",
    "args": ["<your-package-name>"]
  }
}

可用工具

服务器提供：

  • hello_tool ：一个简单的示例工具，它接受一个名称参数并返回问候语

创建新工具

要添加新工具：

  1. 在index.ts中定义工具架构

  2. 将其添加到ListToolsRequestSchema处理程序中的工具数组中

  3. 在CallToolRequestSchema处理程序中添加实现

请参阅hello_tool实现作为示例。

Available Tools

1 tool
hello_toolD

Hello tool

ParametersJSON Schema
NameRequiredDescriptionDefault
nameYesThe name of the person to greet

TDQS

D1.7/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Hello tool' discloses nothing about side effects, return values, or operational behavior, leaving the agent completely uninformed beyond the tool's name.

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

Conciseness2/5

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

The description is extremely short, but this is under-specification rather than effective conciseness. It is a two-word tautology that provides no informative structure or front-loaded value.

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

Completeness2/5

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

While the tool is simple and the schema fully documents its one parameter, the description still fails to state the tool's purpose or expected behavior. An agent may infer from the name and parameter that it greets a person, but the description itself is incomplete.

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?

Schema description coverage is 100%: the only parameter, 'name', is described as 'The name of the person to greet'. This meets the baseline where the schema does the heavy lifting. The description itself adds no additional parameter meaning.

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

Purpose1/5

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

The description 'Hello tool' simply restates the tool name without a verb, resource, or outcome. It does not specify that the tool greets a person or what action it performs, and it fails to distinguish itself from siblings like plan_trip or search_location.

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 no guidance on when to use this tool or when to prefer an alternative. There are no exclusions, conditions, or context clues to help an agent decide between hello_tool and its siblings.

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 observedhello_tool
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

C2.2/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools, making it perfectly clear which tool to use for any task within this server's scope.

Naming Consistency5/5

The single tool name 'hello_tool' follows a consistent verb_noun pattern, and with no other tools to compare, there is no inconsistency in naming conventions.

Tool Count2/5

One tool is generally too few for a server's purpose unless it is extremely trivial, which 'hello_tool' suggests. This feels thin and under-scoped for a typical MCP server, indicating a mismatch in tool count appropriateness.

Completeness1/5

With only a 'hello_tool', the server lacks any meaningful coverage of a domain. It is severely incomplete, as there are no operations for CRUD, lifecycle management, or any substantive workflows, making it inadequate for agent-driven tasks.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers

  • MCP Server Scaffold

    vjouenne76
    F
    license
    B
    quality
    D
    maintenance
    A basic starter project for building Model Context Protocol (MCP) servers that enables standardized interactions between AI systems and various data sources through secure, controlled tool implementations.
    2
    -

  • Hello World MCP FastAPI

    bankszach
    F
    license
    Not graded
    quality
    D
    maintenance
    A minimal Model Context Protocol server built with FastAPI that provides a basic "Hello World" resource and tool. Serves as a starting point for building and validating MCP client integrations with richer resources and tools.
    -

  • mcp-base

    sesopenko
    A
    license
    Not graded
    quality
    D
    maintenance
    A bare-bones FastMCP server template designed to serve as a starting point for building custom Model Context Protocol servers. It provides a foundational structure for implementing tools over HTTP and includes a built-in health check utility.
    GPL 3.0

Appeared in Searches