Skip to main content
Glama
enesjakozh
stevennevins

MCP Server Template

by stevennevins
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

MCP 서버 템플릿

필수 조건

LLM CLI 설치

이 프로젝트를 실행하려면 LLM CLI 설치가 필요합니다. Homebrew를 사용하여 설치할 수 있습니다.

지엑스피1

설치 후 다음을 실행하여 llm 명령을 PATH에서 사용할 수 있는지 확인하세요.

llm --version

Related MCP server: MCP Server Template

시작하기

개발

  1. 종속성 설치:

    npm install

  2. 핫 리로드로 개발 서버를 시작합니다.

    npm run dev

  3. 프로젝트를 빌드하세요:

    npm run build

  4. 테스트 실행:

    npm test

  5. 프로덕션 서버를 시작합니다.

    npm start

건축가 도구

Architect 도구( src/tools/architect.ts )는 아키텍처 설계 피드백을 위해 LLM CLI와 상호 작용할 수 있는 인터페이스를 제공합니다. 대화 컨텍스트를 유지하고 애플리케이션과 LLM CLI 간의 통신을 처리합니다.

특징

  • 여러 상호 작용에서 대화 맥락을 유지합니다.

  • LLM CLI를 통해 명령 실행을 처리합니다.

  • 오류 처리 및 로깅 제공

  • 새로운 대화와 지속적인 토론을 모두 지원합니다.

요구 사항

  • LLM CLI가 설치되어 PATH에 사용 가능해야 합니다(필수 조건 섹션 참조)

  • LLM CLI에 대한 환경 변수는 적절하게 구성되어야 합니다.

테스트

템플릿에는 로컬 테스트를 위한 내장 TestClient와 시각적 디버깅을 위한 MCP Inspector가 포함되어 있습니다.

TestClient 사용

TestClient는 도구를 테스트하는 간단한 방법을 제공합니다.

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();
      }
    );
  });
});

MCP Inspector 사용

템플릿에는 도구의 시각적 디버깅을 위한 MCP 검사기가 포함되어 있습니다.

  1. 검사기를 시작합니다.

    npx @modelcontextprotocol/inspector node dist/index.js

  2. http://localhost:5173 에서 검사기 UI를 엽니다.

검사관은 다음을 제공합니다.

  • 테스트 도구를 위한 시각적 인터페이스

  • 실시간 요청/응답 모니터링

  • 도구 메타데이터 검사

  • 대화형 테스트 환경

커서를 사용한 로컬 테스트

Cursor를 사용하여 로컬로 MCP 서버를 테스트하려면:

  1. 패키지를 빌드하고 연결하세요.

    npm run build
npm run link

  2. 바이너리가 작동하는지 확인하세요.

    npx architect-test-mcp-tool

  3. 커서에 서버를 추가합니다.

    • 커서 설정 열기

    • 기능 탭으로 이동

    • MCP 서버 섹션으로 스크롤하세요

    • "서버 추가"를 클릭하세요

    • "명령" 유형을 선택하세요

    • 이름을 지정합니다(예: "로컬 예제 도구")

    • 명령을 입력하세요: npx architect-test-mcp-tool

    • 확인을 클릭하세요

  4. MCP 서버 섹션에 서버가 실행 중으로 표시되는지 확인하여 Cursor에서 서버가 올바르게 시작되는지 확인하세요.

참고: 코드를 변경한 경우 다시 빌드하고 다시 링크하는 것을 잊지 마세요.

npm run build
npm run link

테스트가 끝나면 패키지의 연결을 해제할 수 있습니다.

npm run unlink

이렇게 하면 개발 중에 생성된 글로벌 심볼릭 링크가 제거됩니다.

문제 해결

MCP Inspector 사용

MCP Inspector는 MCP 서버 디버깅 및 검사에 유용한 도구입니다. 사용 방법은 다음과 같습니다.

  1. 먼저 프로젝트를 빌드하세요.

    npm run build

  2. 검사기를 실행합니다.

    npx @modelcontextprotocol/inspector node dist/index.js

검사기는 다음을 수행할 수 있는 웹 인터페이스를 제공합니다.

  • 사용 가능한 모든 도구와 해당 스키마 보기

  • 테스트 도구는 대화형으로 호출합니다.

  • 요청/응답 페이로드 검사

  • 서버와 클라이언트 간 통신 문제 디버깅

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

Related MCP Connectors

Related MCP Servers

Appeared in Searches