Jentic
OfficialПлагин Jentic MCP
Зачем использовать Jentic MCP?
Jentic MCP позволяет разработчикам быстро находить и интегрировать внешние API и рабочие процессы — без необходимости писать или поддерживать какой-либо API-специфичный код. Используя протокол MCP и агентскую среду выполнения Jentic, разработчики могут:
Выполняйте поиск API и рабочих процессов по возможностям, а не по поставщику или реализации.
Мгновенно создавайте примеры кода интеграции, не зависящие от конкретных деталей API.
Избегайте шаблонного кода и сократите объем обслуживания, полагаясь на стандартизированную, декларативную интеграцию.
Сосредоточьтесь на создании функций, в то время как Jentic MCP справляется со сложностью взаимодействия API.
Related MCP server: agent-zone-mcp
API-инструменты
Плагин Jentic MCP предоставляет следующие инструменты:
search_apis: Поиск API в каталоге Jentic, соответствующих определенным функциональным потребностямload_execution_info: Получить подробные спецификации для API и операций из каталога Jentic. Это будет включать информацию об аутентификации, которую вам может потребоваться предоставить в конфигурацииmcpServers.jentic.env.execute: выполнить определенную операцию API или рабочего процесса.
Начиная
Рекомендуемый метод — запустить сервер напрямую из репозитория GitHub с помощью uvx . Сначала вам нужно будет установить uv с помощью:
brew install uv или pip install uv
Получите свой Jentic UUID
Чтобы использовать Jentic SDK, сначала необходимо получить Jentic UUID. Самый простой способ — использовать Jentic CLI. При желании можно включить адрес электронной почты для более высоких лимитов скорости и раннего доступа к новым функциям.
pip install jentic
jentic register --email '<your_email>'Эта команда выведет ваш UUID и команду экспорта для его установки в вашей среде:
export JENTIC_UUID=<your-jentic-uuid>Установите Jentic UUID в конфигурации клиента MCP, как показано ниже.
Расположение файла конфигурации зависит от используемого вами клиента и вашей ОС. Некоторые общие примеры:
Виндсерфинг :
~/.codeium/windsurf/mcp_config.jsonРабочий стол Клода :
~/Library/Application Support/Claude/claude_desktop_config.jsonКод Клода :
~/.claude.jsonКурсор :
~/cursor/.mcp.json
Для других клиентов проверьте документацию вашего клиента, чтобы узнать, как добавлять серверы MCP.
{
"mcpServers": {
"jentic": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp",
"mcp"
],
"env": {
"JENTIC_UUID": "<your-jentic-uuid>"
}
}
}
}Примечание: После сохранения файла конфигурации может потребоваться перезапустить клиентское приложение (Windsurf, Claude Desktop), чтобы изменения вступили в силу.
Использование инструмента MCP
После запуска сервера MCP вы можете легко использовать инструменты MCP в своем агенте LLM для обнаружения и выполнения API и рабочих процессов.
search_apis: Поиск API в каталоге Jentic, соответствующих определенным функциональным потребностямload_execution_info: Получить подробные спецификации для API и операций из каталога Jentic. Это будет включать информацию об аутентификации, которую вам может потребоваться предоставить в конфигурацииmcpServers.jentic.env.execute: выполнить определенную операцию API или рабочего процесса.
Переменные среды
При использовании API, требующего аутентификации, инструмент load_execution_info опишет требуемые переменные среды. Вы можете использовать переменные среды через командную строку в Windsurf, хотя в некоторых клиентах, таких как Claude Desktop, вам нужно будет добавить их в конфигурацию MCP:
{
"mcpServers": {
"jentic": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp",
"mcp"
],
"env": {
"DISCORD_BOTTOKEN=": "YOUR BOT TOKEN"
}
}
}
}Альтернатива (использование локального пути для разработки):
Используйте это, если вы активно разрабатываете плагин MCP локально. Замените /path/to/your/project/mcp на абсолютный путь к каталогу вашего проекта.
{
"mcpServers": {
"jentic": {
"command": "uvx",
"args": [
"--from",
"/path/to/your/project/mcp",
"mcp"
]
}
}
}Необязательно: добавьте переменную среды JENTIC_API_URL в файл mcp_config.json , чтобы указать на конкретный API Jentic (работает с обоими методами):
{
"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/"
}
}
}
}После настройки перезапустите Windsurf, и инструменты Jentic MCP станут доступны.
Вы можете отслеживать журналы, сгенерированные локально работающим сервером MCP, выполнив:
tail /path/to/mcp/jentic_ark2_mcp.logУстановка
Установка через Smithery
Чтобы автоматически установить плагин Jentic для Claude Desktop через Smithery :
npx -y @smithery/cli install @jentic/jentic-tools --client claudeРучная установка
Убедитесь, что у вас установлен pdm ( pipx install pdm ).
Чтобы установить пакет и его зависимости для разработки:
# From the project root directory (e.g., /Users/kc/c/sdk/mcp)
pdm install -G devЗапуск сервера MCP
Плагин Jentic MCP предназначен для запуска с использованием uvx , который управляет настройкой среды и выполнением.
Режим по умолчанию (Stdio)
Запустите плагин MCP напрямую с помощью uvx , указав каталог проекта в качестве источника с помощью --from и скрипта mcp :
Из локального пути (развитие):
# 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 . mcpИз удаленного репозитория (рекомендуется для общего использования):
uvx --from \
git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp \
mcpПри этом автоматически используется команда serve --transport stdio по умолчанию, определенная в обратном вызове скрипта mcp .
HTTP-режим
Чтобы запустить сервер в режиме HTTP (например, для тестирования с помощью claude-cli ):
Из локального пути (развитие):
# 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 8080Из удаленного репозитория (рекомендуется):
uvx --from \
git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp \
mcp serve --transport http --port 8080Запуск из удаленного репозитория Git
Вы также можете запустить сервер MCP напрямую из URL-адреса репозитория Git, не клонируя его локально, используя uvx --from :
# 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.tomlЭта команда извлекает указанную версию, устанавливает ее зависимости во временной среде и запускает команду по умолчанию (которая называется serve --transport stdio ).
Вы можете добавить другие аргументы, такие как --log-level DEBUG или --mock после фрагмента URL:
uvx --from \
git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp \
--log-level DEBUG --mockДля запуска в режиме HTTP из удаленного источника:
uvx --from \
git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp \
serve --transport http --port 8080Другие варианты
Ведение журнала
# 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.logРежим имитации
Включите режим имитации для разработки без подключения к фактическому центру знаний API Jentic:
# 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 --mockПеременные среды
Укажите переменные среды с помощью файла .env :
# 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 .envИспользование с Клодом
Плагин MCP можно использовать с Claude или другими LLM, которые поддерживают спецификацию MCP:
Запуск из удаленного репозитория (рекомендуется):
# 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:8000Запуск из локального пути (разработка):
# 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:8000Разработка
Подробные инструкции по разработке см. на сайте CLAUDE.md.
Структура пакета
src/mcp/: Основной пакет MCPtransport/: Реализации транспорта (HTTP, stdio)mock/: Поставщики фиктивных данных для разработкиtools.py: Определения инструментовhandlers.py: Обработчики запросовmain.py: точки входа CLIadapters/: Реализации адаптеровcore/: Основная функциональность
tests/: Тестовый набор
Тестирование
# Ensure dev dependencies are installed: pdm install -G dev
pdm run testЛинтинг и форматирование
Использует ruff , black , isort , mypy через скрипты pdm.
# Run all linters/formatters
pdm run lint
# Run only ruff
pdm run linterЛицензия
Запатентованная разработка - Jentic
Available Tools
3 toolsexecuteC
Perform the chosen action for the user using the provided details (if any are needed).
| Name | Required | Description | Default |
|---|---|---|---|
| execution_type | Yes | Specify whether to execute an 'operation' or a 'workflow'. | |
| inputs | Yes | The input parameters required by the operation or workflow. | |
| uuid | Yes | The UUID of the operation or workflow to execute. |
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| operation_uuids | Yes | The UUIDs of the operations to include in the configuration files. | |
| workflow_uuids | Yes | The UUIDs of the workflows to include in the configuration files. |
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| capability_description | Yes | Natural language description of the action needed (e.g., 'send emails', 'weather forecasting', 'natural language processing') | |
| keywords | No | Optional list of specific keywords to help narrow down the search | |
| max_results | No | Maximum number of actions to return |
TDQS
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.
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.
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.
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.
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.
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.
3 tool updates
v1.0.0- First observed
execute - First observed
load_execution_info - First observed
search_apis
TDQS
Scored across 3 tools
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.
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.
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.
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.
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