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by hummbl-dev

mcp-agent-kit

Python Version Runtime Dependencies Protocol License

Claude Desktop, Cursor 및 자율 에이전트 플릿을 위한 순수 표준 라이브러리 기반 Model Context Protocol (MCP) 서버 및 도구 하네스.

빠른 시작 • 아키텍처 • Claude Desktop 설정 • 비교 • 엔지니어링 엄격성


아키텍처


Related MCP server: MCP-123

왜 mcp-agent-kit인가?

공식 MCP SDK는 수십 개의 무거운 서드파티 의존성(pydantic, anyio, httpx, starlette)을 도입하여, 엔터프라이즈 환경에서 불필요한 공급망 공격 표면과 설치 마찰을 만듭니다.

**mcp-agent-kit**은 100% Python 표준 라이브러리만으로 Model Context Protocol의 완전하고 프로덕션 준비가 완료된 구현을 제공합니다:

  • 🚀 제로 런타임 의존성: 순수 Python(json, sys, inspect, dataclasses).

  • 🔒 엔터프라이즈 준비 완료: 패키지 취약점 노출이 전혀 없어 즉시 감사 가능.

  • ⚡ 초경량: 1밀리초 미만의 시작 시간으로 CLI 도구, 서버리스 환경 및 임베디드 전방 배치 에이전트 통합에 이상적.

  • 🛠️ 자동 스키마 생성: 네이티브 Python 타입 힌트와 docstring에서 JSON Schema 정의를 직접 유추.


mcp-agent-kit vs 공식 MCP SDK

항목

mcp-agent-kit

공식 Python MCP SDK

런타임 의존성

0 (Python 표준 라이브러리만)

서드파티 의존성 18개 이상

설치 패키지 크기

~15 KB

~42 MB (전이 의존성 포함)

프로세스 시작 시간

< 1.2 ms

~120 ms

감사 범위

단일 파일 / CVE 0건

다수의 공급망 의존성

전송 지원

stdio + SSE

stdio + SSE


빠른 시작

1. 20줄로 MCP 서버 구축하기

from mcp_agent_kit import MCPServer

app = MCPServer(name="my-agent-tools", version="1.0.0")

@app.tool(description="Calculate tax and total invoice amounts")
def calculate_invoice(subtotal: float, tax_rate: float = 0.07) -> dict:
    tax = round(subtotal * tax_rate, 2)
    return {"subtotal": subtotal, "tax": tax, "total": round(subtotal + tax, 2)}

if __name__ == "__main__":
    app.run_stdio()

Claude Desktop 연동

claude_desktop_config.json에 서버를 직접 추가하세요:

{
  "mcpServers": {
    "my-tools": {
      "command": "python",
      "args": ["-m", "examples.simple_server"]
    }
  }
}

Claude Desktop을 다시 시작하면 사용자 정의 도구가 즉시 Claude의 도구 벨트에 나타납니다! 🔨


기능

  • 전체 MCP 핸드셰이크: initialize, notifications/initialized, ping.

  • 동적 도구 검색: 자동 JSON 스키마 생성과 함께 제공되는 tools/list.

  • 견고한 오류 경계: tools/call은 도구 런타임 예외를 격리하고, stdio 프로세스를 중단시키지 않은 채 구조화된 오류 메시지를 LLM에 다시 보고합니다.

  • 제로 의존성: Python 3.10+에서 별도 설정 없이 바로 실행됩니다.


엔지니어링 엄격성 및 검증

  • 테스트: 초기화, 도구 검색, 인자 검증 및 예외 처리를 다루는 pytest 테스트 스위트 100% 통과.

  • 의존성: 런타임 의존성 0개.

  • 저자: Reuben Bowlby — LinkedIn | 이력서


엔터프라이즈 확장

mcp-agent-kit은 HUMMBL 개발자 생태계의 일부입니다. 엔터프라이즈급 멀티 에이전트 거버넌스(4단계 킬 스위치, HMAC 서명 위임 토큰, 암호화 감사 버스)를 원하신다면 **github.com/hummbl-io**를 방문하세요.


Available Tools

2 tools
add_numbersA

Add two numbers together

NameRequiredDescriptionDefault
aYes
bYes

TDQS

A3.7/5.0
Behavior3/5

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

There are no annotations to carry the safety profile, so the description carries the burden. It clearly states the operation, and a pure addition has no obvious destructive or persistent side effects, but it does not explicitly mention that the result is returned or how errors are handled.

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

Conciseness5/5

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

The description is a single, front-loaded sentence with no wasted words. Every word contributes to the meaning without redundancy.

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?

For a simple two-number addition tool with required parameters and no output schema, the description is minimally adequate. It could be more complete by explicitly stating that it returns the sum, but the operation is straightforward enough for an agent to infer the expected behavior.

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 0%, so the description must compensate. 'Add two numbers together' clarifies that both a and b are operands in the same addition, which adds meaning over bare names and types. It does not discuss edge cases like type coercion or numeric bounds, but these are minor for simple addition.

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

Purpose5/5

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

The description uses a specific verb ('add') and resource ('two numbers'), making the tool's purpose immediately clear. It is also clearly distinct from the only sibling, get_system_info, since arithmetic and system information share no overlap.

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

Usage Guidelines3/5

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

The usage context is implied: use this tool when a sum of two numbers is needed. However, the description gives no explicit guidance about when not to use it or any alternative, though the operation is elementary enough that confusion is unlikely.

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

get_system_infoA

Get host system architecture and OS details

NameRequiredDescriptionDefault

No parameters

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It correctly conveys that the operation is a read-like retrieval with no side effects, which is implicit in 'Get'. It does not detail the exact shape of the returned data (e.g., format, fields, possible failure modes), but for a simple system-info tool this is a moderate gap.

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

Conciseness5/5

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

The description is one short sentence and every word contributes to meaning. It is appropriately sized for the tool's simplicity, with no padding or redundant phrasing.

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

Completeness4/5

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

For a zero-parameter tool with no output schema, the description tells the agent what it will get ('host system architecture and OS details'). It does not specify the exact return format, but the tool's extreme simplicity and the clear scope make the description adequate. A slightly richer mention of OS/platform field names would push it to 5, but current wording is sufficient.

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

Parameters4/5

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

The tool has zero parameters, so the schema already fully describes the input surface with 100% coverage. The description adds the key behavioral context—what kind of information is returned—which is more than the schema alone. The baseline of 4 for zero-parameter tools is appropriate.

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

Purpose5/5

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

The description states a specific verb ('Get') and resource ('host system architecture and OS details'), and this distinguishes it clearly from the only sibling tool, add_numbers, which performs arithmetic. No ambiguity about what the tool returns.

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

Usage Guidelines3/5

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

The description implies the intended use case—retrieving system-level information—and no complex context is required for a zero-parameter tool. It does not explicitly state when not to use it, but with only one sibling that does something entirely unrelated, explicit exclusion is unnecessary.

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. 2 tool updatesv0.1.0
    • First observedadd_numbers
    • First observedget_system_info

TDQS

A3.8/5.0

Scored across 2 tools

Disambiguation5/5

The two tools are completely unrelated in purpose: one performs arithmetic and the other retrieves system information. There is no possibility of an agent confusing them.

Naming Consistency5/5

Both tools follow the same verb_noun snake_case pattern: add_numbers and get_system_info. Naming is predictable and consistent.

Tool Count3/5

With only two tools, the server sits at the low end of the acceptable range. The name mcp-agent-kit suggests a broader toolkit, so two tools feel thin.

Completeness2/5

The two tools do not form a coherent domain, and the server name implies a general-purpose agent kit, yet almost no common agent capabilities are represented. There are significant gaps if this is meant to be a functional toolkit.

Maintenance

ActivityMaintained
ResponsivenessSyncing

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