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젠틱 MCP 플러그인

대장간 배지

왜 Jentic MCP를 사용해야 하나요?

Jentic MCP는 개발자가 API별 코드를 작성하거나 유지 관리할 필요 없이 외부 API와 워크플로를 신속하게 탐색하고 통합할 수 있도록 지원합니다. MCP 프로토콜과 Jentic의 에이전트 런타임을 활용하여 개발자는 다음과 같은 작업을 수행할 수 있습니다.

  • 공급업체나 구현이 아닌 기능별로 API와 워크플로를 검색하세요.

  • 특정 API 세부 정보에 구애받지 않는 통합 코드 샘플을 즉시 생성합니다.

  • 표준화되고 선언적인 통합을 사용하여 보일러플레이트를 피하고 유지 관리를 줄이세요.

  • Jentic MCP가 API 상호작용의 복잡성을 처리하는 동안, 기능 구축에 집중하세요.

Related MCP server: agent-zone-mcp

API 도구

Jentic MCP 플러그인은 다음과 같은 도구를 제공합니다.

  1. search_apis : Jentic 디렉토리에서 특정 기능 요구 사항과 일치하는 API를 검색합니다.

  2. load_execution_info : Jentic 디렉터리에서 API 및 작업에 대한 자세한 사양을 가져옵니다. 여기에는 mcpServers.jentic.env 구성에 제공해야 할 인증 정보가 포함됩니다.

  3. execute : 특정 API 또는 워크플로 작업을 실행합니다.

시작하기

권장하는 방법은 uvx 사용하여 GitHub 저장소에서 직접 서버를 실행하는 것입니다. 먼저 다음을 사용하여 uv 설치해야 합니다.

brew install uv 또는 pip install uv

Jentic UUID 받기

Jentic SDK를 사용하려면 먼저 Jentic UUID를 받아야 합니다. 가장 쉬운 방법은 Jentic CLI를 사용하는 것입니다. 더 높은 요금 한도 및 새로운 기능 사전 체험을 위해 이메일 주소를 추가 할 수도 있습니다.

지엑스피1

이렇게 하면 UUID가 출력되고 환경에 맞게 설정할 수 있는 내보내기 명령이 실행됩니다.

export JENTIC_UUID=<your-jentic-uuid>

아래와 같이 MCP 클라이언트 구성에서 Jentic UUID를 설정합니다.

구성 파일의 위치는 사용 중인 클라이언트와 OS에 따라 다릅니다. 몇 가지 일반적인 예는 다음과 같습니다.

  • 윈드서핑 : ~/.codeium/windsurf/mcp_config.json

  • Claude Desktop : ~/Library/Application Support/Claude/claude_desktop_config.json

  • 클로드 코드 : ~/.claude.json

  • 커서 : ~/cursor/.mcp.json

다른 클라이언트의 경우 MCP 서버를 추가하는 방법은 클라이언트 설명서를 확인하세요.

{
    "mcpServers": {
        "jentic": {
            "command": "uvx",
            "args": [
                "--from",
                "git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp",
                "mcp"
            ],
            "env": {
                "JENTIC_UUID": "<your-jentic-uuid>"
            }
        }
    }
}

참고: 구성 파일을 저장한 후 변경 사항을 적용하려면 클라이언트 애플리케이션(Windsurf, Claude Desktop)을 다시 시작해야 할 수도 있습니다.

MCP 도구 사용

MCP 서버가 실행되면 LLM 에이전트의 MCP 도구를 사용하여 API와 워크플로를 쉽게 검색하고 실행할 수 있습니다.

  1. search_apis : Jentic 디렉토리에서 특정 기능 요구 사항과 일치하는 API를 검색합니다.

  2. load_execution_info : Jentic 디렉터리에서 API 및 작업에 대한 자세한 사양을 가져옵니다. 여기에는 mcpServers.jentic.env 구성에 제공해야 할 인증 정보가 포함됩니다.

  3. execute : 특정 API 또는 워크플로 작업을 실행합니다.

환경 변수

인증이 필요한 API를 사용할 때 load_execution_info 도구는 필요한 환경 변수를 설명합니다. Windsurf에서는 명령줄을 통해 환경 변수를 설정할 수 있지만, Claude Desktop과 같은 일부 클라이언트에서는 MCP 설정에 환경 변수를 추가해야 합니다.

{
    "mcpServers": {
        "jentic": {
            "command": "uvx",
            "args": [
                "--from",
                "git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp",
                "mcp"
            ],
            "env": {
                "DISCORD_BOTTOKEN=": "YOUR BOT TOKEN"
            }
        }
    }
}

대안(개발을 위한 로컬 경로 사용):

로컬에서 MCP 플러그인을 적극적으로 개발하는 경우 이 옵션을 사용하세요. /path/to/your/project/mcp 프로젝트 디렉터리의 절대 경로로 바꾸세요.

{
    "mcpServers": {
        "jentic": { 
            "command": "uvx",
            "args": [
                "--from",
                "/path/to/your/project/mcp",
                "mcp" 
            ]
        }
    }
}

선택 사항: mcp_config.json 파일에 JENTIC_API_URL 환경 변수를 추가하여 특정 Jentic API를 가리키도록 합니다(두 가지 방법 모두 적용 가능):

{
    "mcpServers": {
        "jentic": {
            "command": "uvx",
            "args": [
                "--from",
                "git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp",
                "mcp"
            ],
            "env": {
                "JENTIC_API_URL": "https://your-jentic-api.url/"
            }
        }
    }
}

구성이 완료되면 Windsurf를 다시 시작하면 Jentic MCP 도구를 사용할 수 있습니다.

다음을 실행하여 로컬로 실행 중인 MCP 서버에서 생성된 로그를 추적할 수 있습니다.

tail /path/to/mcp/jentic_ark2_mcp.log

설치

Smithery를 통해 설치

Smithery를 통해 Claude Desktop용 Jentic 플러그인을 자동으로 설치하려면:

npx -y @smithery/cli install @jentic/jentic-tools --client claude

수동 설치

pdm 설치되어 있는지 확인하세요( pipx install pdm ).

개발을 위해 패키지와 종속성을 설치하려면:

# From the project root directory (e.g., /Users/kc/c/sdk/mcp)
pdm install -G dev

MCP 서버 실행

Jentic MCP 플러그인은 환경 설정 및 실행을 처리하는 uvx 사용하여 실행되도록 설계되었습니다.

기본 모드(Stdio)

--from 과 mcp 스크립트를 사용하여 프로젝트 디렉토리를 소스로 지정하고 uvx 사용하여 MCP 플러그인을 직접 실행합니다.

로컬 경로(개발)에서:

# Use --from with the project directory and specify the 'mcp' script
uvx --from /path/to/your/project/mcp mcp

# Or, if running from within the project directory:
uvx --from . mcp

원격 저장소에서(일반적인 용도로 권장):

uvx --from \
  git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp \
  mcp

이렇게 하면 mcp 스크립트 콜백에 정의된 기본 serve --transport stdio 명령이 자동으로 사용됩니다.

HTTP 모드

HTTP 모드에서 서버를 실행하려면(예: claude-cli 로 테스트하는 경우):

로컬 경로(개발)에서:

# Default HTTP (port 8010)
uvx --from /path/to/your/project/mcp mcp serve --transport http

# With custom port
uvx --from /path/to/your/project/mcp mcp serve --transport http --port 8080

# With custom host
uvx --from /path/to/your/project/mcp mcp serve --transport http --host 0.0.0.0 --port 8080

원격 저장소에서(권장):

uvx --from \
  git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp \
  mcp serve --transport http --port 8080

원격 Git 저장소에서 실행

uvx --from 사용하여 로컬로 복제하지 않고도 Git 저장소 URL에서 직접 MCP 서버를 실행할 수도 있습니다.

# Example from a specific branch and subdirectory
uvx --from \
  git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp

# Explanation:
# - git+https://... .git : The repository URL
# - @main   : The branch, tag, or commit hash
# - #subdirectory=mcp     : The folder within the repo containing the pyproject.toml

이 명령은 지정된 버전을 가져오고, 임시 환경에 종속성을 설치하고, 기본 명령( serve --transport stdio )을 실행합니다.

URL 조각 뒤에 --log-level DEBUG 또는 --mock 과 같은 다른 인수를 추가할 수 있습니다.

uvx --from \
  git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp \
  --log-level DEBUG --mock

원격 소스에서 HTTP 모드로 실행하려면:

uvx --from \
  git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp \
  serve --transport http --port 8080

기타 옵션

벌채 반출

# Set logging level (applies to default stdio or explicit serve)
uvx --from /path/to/your/project/mcp mcp --log-level DEBUG
uvx --from /path/to/your/project/mcp mcp serve --transport http --log-level DEBUG

# Log to file (applies to default stdio or explicit serve)
uvx --from /path/to/your/project/mcp mcp --log-file jentic_mcp.log
uvx --from /path/to/your/project/mcp mcp serve --transport http --log-file jentic_mcp.log

모의 모드

실제 Jentic API 지식 허브에 연결하지 않고도 개발을 위한 모의 모드를 활성화합니다.

# Mock mode with default stdio
uvx --from /path/to/your/project/mcp mcp --mock

# Mock mode with explicit HTTP
uvx --from /path/to/your/project/mcp mcp serve --transport http --mock

환경 변수

.env 파일을 사용하여 환경 변수를 제공합니다.

# Env file with default stdio
uvx --from /path/to/your/project/mcp mcp --env-file .env

# Env file with explicit HTTP
uvx --from /path/to/your/project/mcp mcp serve --transport http --env-file .env

Claude와 함께 사용

MCP 플러그인은 Claude 또는 MCP 사양을 지원하는 다른 LLM과 함께 사용할 수 있습니다.

원격 저장소에서 실행(권장):

# Run the server in HTTP mode first
uvx --from \
  git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp \
  mcp serve --transport http --port 8000

# Then connect claude-cli
claude-cli --mcp http://localhost:8000

지역 경로에서 실행(개발):

# Run the server in HTTP mode first
uvx --from /path/to/your/project/mcp mcp serve --transport http --port 8000

# Then connect claude-cli
claude-cli --mcp http://localhost:8000

개발

자세한 개발 지침은 CLAUDE.md를 참조하세요.

패키지 구조

  • src/mcp/ : 메인 MCP 패키지

    • transport/ : 전송 구현(HTTP, stdio)

    • mock/ : 개발을 위한 모의 데이터 제공자

    • tools.py : 도구 정의

    • handlers.py : 요청 핸들러

    • main.py : CLI 진입점

    • adapters/ : 어댑터 구현

    • core/ : 핵심 기능

  • tests/ : 테스트 모음

테스트

# Ensure dev dependencies are installed: pdm install -G dev
pdm run test

린팅 및 포맷팅

pdm 스크립트를 통해 ruff , black , isort , mypy 사용합니다.

# Run all linters/formatters
pdm run lint

# Run only ruff
pdm run linter

특허

독점 - 젠틱

Available Tools

3 tools
executeC

Perform the chosen action for the user using the provided details (if any are needed).

ParametersJSON Schema
NameRequiredDescriptionDefault
execution_typeYesSpecify whether to execute an 'operation' or a 'workflow'.
inputsYesThe input parameters required by the operation or workflow.
uuidYesThe UUID of the operation or workflow to execute.

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states 'perform the chosen action' which implies a write/mutation operation, but doesn't disclose critical behavioral traits: whether this is synchronous/asynchronous, what permissions are required, whether it's idempotent, what happens on failure, or what the response contains. For a tool that appears to execute potentially complex operations/workflows, this is a significant gap.

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 a single, efficient sentence that gets straight to the point without unnecessary words. However, this conciseness comes at the cost of being under-specified for a tool with three required parameters and no annotations - it could benefit from one more clarifying sentence about what gets executed.

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?

For a tool with 3 required parameters (including a nested object), no annotations, and no output schema, the description is inadequate. It doesn't explain what types of actions can be executed, what the expected outcomes are, or provide any error handling context. The agent would struggle to use this tool effectively without trial and error.

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%, so the schema already documents all three parameters thoroughly. The description adds no parameter-specific information beyond the generic 'using the provided details' - it doesn't clarify the relationship between execution_type, uuid, and inputs, or provide examples of valid input objects. Baseline 3 is appropriate when the schema does all the heavy lifting.

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

Purpose2/5

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

The description 'Perform the chosen action for the user using the provided details' is tautological - it essentially restates the tool name 'execute' without specifying what kind of actions or resources are involved. While it mentions 'chosen action' and 'provided details', it doesn't clarify whether this executes operations, workflows, scripts, or other entities, nor does it distinguish this from sibling tools like 'load_execution_info' or 'search_apis'.

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 guidance - it mentions 'chosen action' and 'provided details' but gives no explicit when-to-use criteria, no prerequisites, and no comparison to alternatives like 'load_execution_info' (which presumably loads execution information rather than performing execution) or 'search_apis'. The agent must infer usage from the parameter schema alone.

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

load_execution_infoC

Get more details about a specific action (like what information it needs from the user) before confirming you want to run it. Usually used if the action requires specific inputs. Coding Agents: To provide tools to an LLM that you have selected at runtime, use this tool to retrieve the necessary information and save it to 'jentic.json' at the root of your project.

ParametersJSON Schema
NameRequiredDescriptionDefault
operation_uuidsYesThe UUIDs of the operations to include in the configuration files.
workflow_uuidsYesThe UUIDs of the workflows to include in the configuration files.

TDQS

C2.5/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden but offers limited behavioral insight. It mentions retrieving information and saving to a file, but doesn't disclose critical traits like whether this is a read-only operation, if it modifies state, authentication needs, rate limits, or error handling. The description adds some context but leaves significant gaps.

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

Conciseness3/5

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

The description is moderately concise but not optimally structured. The first sentence clearly states the purpose, but the second sentence adds implementation details for coding agents that may not apply to all users. The information is somewhat front-loaded but could be more focused.

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?

Given no annotations and no output schema, the description should provide more complete context. It mentions retrieving details and saving to a file, but doesn't explain what format the details take, what 'jentic.json' contains, or what happens if parameters are invalid. For a tool with 2 required parameters and mutation implications, this is inadequate.

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%, so parameters are well-documented in the schema. The description doesn't add meaningful semantic context beyond what the schema provides about operation_uuids and workflow_uuids. It mentions 'configuration files' but doesn't clarify how parameters relate to this output.

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

Purpose3/5

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

The description states the tool 'Get more details about a specific action' which indicates its purpose, but it's vague about what 'details' means and doesn't clearly differentiate from sibling tools like 'execute' or 'search_apis'. It mentions saving to 'jentic.json' which adds specificity but confuses the core purpose with implementation details for coding agents.

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 some guidance ('Usually used if the action requires specific inputs') but lacks explicit when-to-use vs. alternatives. It doesn't clarify when to choose this over 'execute' or 'search_apis', and the coding agent note is situational rather than general usage guidance.

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

search_apisA

Search for available actions or information based on what the user wants to do (e.g., 'find Discord servers', 'send a message'). Use this first to understand what's possible.

ParametersJSON Schema
NameRequiredDescriptionDefault
capability_descriptionYesNatural language description of the action needed (e.g., 'send emails', 'weather forecasting', 'natural language processing')
keywordsNoOptional list of specific keywords to help narrow down the search
max_resultsNoMaximum number of actions to return

TDQS

A3.6/5.0
Behavior2/5

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. It mentions the tool searches for actions or information but lacks details on behavioral traits such as response format, error handling, rate limits, or authentication needs. For a search tool with zero annotation coverage, this is a significant gap, though it does imply it returns results (e.g., 'to return' in the schema).

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, with two sentences that efficiently convey purpose and usage guidelines. Every sentence earns its place by providing essential information without redundancy. It could be slightly more concise by integrating examples more seamlessly, but overall it's well-structured.

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 tool's moderate complexity (3 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It covers purpose and usage well but lacks behavioral details like return format or error handling. Without annotations or an output schema, the description should do more to compensate, making it minimally viable but 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%, so the schema already documents all three parameters thoroughly. The description does not add any additional meaning beyond what the schema provides, such as explaining how 'capability_description' interacts with 'keywords' or detailing search algorithms. Baseline 3 is appropriate when the schema does the heavy lifting.

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: 'Search for available actions or information based on what the user wants to do.' It provides a specific verb ('search') and resource ('available actions or information'), with examples like 'find Discord servers' and 'send a message' to illustrate usage. However, it doesn't explicitly distinguish this from sibling tools like 'execute' or 'load_execution_info', which prevents 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 Guidelines5/5

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

The description provides explicit guidance on when to use this tool: 'Use this first to understand what's possible.' This clearly indicates it should be employed as an initial step to discover capabilities before invoking other tools, effectively differentiating it from siblings like 'execute' (which likely performs actions) and 'load_execution_info' (which might retrieve details).

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. 3 tool updatesv1.0.0
    • First observedexecute
    • First observedload_execution_info
    • First observedsearch_apis

TDQS

C2.9/5.0

Scored across 3 tools

Disambiguation4/5

The tools have distinct primary purposes: 'search_apis' discovers available actions, 'load_execution_info' retrieves details for a specific action, and 'execute' performs the action. There is minor potential overlap between 'load_execution_info' and 'execute' in handling action details, but the descriptions clarify their sequential workflow roles.

Naming Consistency3/5

The naming is mixed: 'search_apis' and 'load_execution_info' use snake_case with descriptive verbs, while 'execute' is a single verb without a noun. This inconsistency in structure (two tools follow a verb_noun pattern, one does not) reduces predictability, though the names remain readable.

Tool Count4/5

With 3 tools, the count is reasonable for a server focused on action discovery and execution. It feels slightly thin but covers core workflows (search, detail retrieval, execution), avoiding bloat. A few more tools might enhance completeness, but this is a solid minimal set.

Completeness3/5

The tool set covers a basic workflow (search, load info, execute) for action-based operations, but there are notable gaps. For example, there's no tool for managing or listing previously executed actions, error handling, or status checks, which could limit agent effectiveness in more complex scenarios.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

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