Jentic
БесплатноНе проверенEnables AI assistants to discover and execute external APIs and workflows through a Python SDK that leverages the Open Agentic Knowledge repository for standard
Описание
Enables AI assistants to discover and execute external APIs and workflows through a Python SDK that leverages the Open Agentic Knowledge repository for standardized API access and execution.
README
Jentic empowers AI-agent builders to discover and integrate external APIs and workflows rapidly—without writing or maintaining any API-specific code.
This mono-repo contains:
- Jentic SDK – a Python library for searching, loading and executing APIs / workflows, plus helpers for turning those actions into LLM tools.
- Jentic MCP Plugin – an MCP server that exposes the same capabilities to any MCP-compatible client (Windsurf, Claude Desktop, Cursor, …).
See the dedicated READMEs for full details:
- python/README.md – SDK usage & API reference
- mcp/README.md – MCP server setup & configuration
The SDK is backed by the data in the Jentic Public APIs repository.
Quick start
1. Install Python package
pip install jentic
2. Obtain your Agent API Key
Visit https://app.jentic.com/sign-in to create an agent and copy the key.
export JENTIC_AGENT_API_KEY=<your-agent-api-key>
3. Use the SDK
import asyncio
from jentic import Jentic, SearchRequest, LoadRequest, ExecutionRequest
async def main():
client = Jentic()
# 1️⃣ find a capability
results = await client.search(SearchRequest(query="send a Discord DM"))
entity_id = search.results[0].id # op_... or wf_...
# 2️⃣ load details (inspect schemas / auth, see inputs for operations)
resp = await client.load(LoadRequest(ids=[entity_id]))
inputs = resp.tool_info[entity_id].inputs
print (inputs)
# 3️⃣ run it
result = await client.execute(
ExecutionRequest(id=entity_id, inputs={"recipient_id": "123", "content": "Hello!"})
)
print(result)
asyncio.run(main())
4. Integrate with your LLM agent (optional)
If you need fully-formed tool definitions for Anthropic or OpenAI models, use the runtime helpers:
from jentic.lib.agent_runtime import AgentToolManager
manager = AgentToolManager(format="anthropic")
tools = manager.generate_tool_definitions() # pass these to the LLM
result = await manager.execute_tool("discord_send_message",
{"recipient_id": "123", "content": "Hi"})
print(result)
Using the MCP plugin
It is reccomended to use the Remote MCP server. See instructions here.
If you would prefer to use the legacy local MCP server, follow the instructions in mcp/README.md.
uvx --from \
git+https://github.com/jentic/jentic-sdks.git@main#subdirectory=mcp \
mcp
Then configure your MCP-compatible client to point at the running server (see the sub-README for sample client configs).
Установка Jentic
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/jentic/jentic-sdksFAQ
Jentic MCP бесплатный?
Да, Jentic MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Jentic?
Нет, Jentic работает без API-ключей и переменных окружения.
Jentic — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Jentic в Claude Desktop, Claude Code или Cursor?
Открой Jentic на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
Похожие MCP
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
автор: modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
автор: xuzexin-hzCompare Jentic with
Не уверен что выбрать?
Найди свой стек за 60 секунд
Автор?
Embed-бейдж для README
Похожее
Все в категории ai
