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MCP Server

Jentic

Jentic

22
GitHub Stars
10/3/2025
Last Updated
MCP Server Configuration
1{
2 "name": "jentic",
3 "command": "uvx",
4 "args": [
5 "--from",
6 "git+https://github.com/jentic/jentic-tools.git@main#subdirectory=mcp",
7 "mcp"
8 ],
9 "env": {
10 "JENTIC_UUID": ""
11 }
12}
JSON12 lines

README Documentation

Jentic SDK & MCP Plugin [Beta]

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:

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

To expose the same capabilities via MCP, 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).

Quick Install

Quick Actions

Key Features

Model Context Protocol
Secure Communication
Real-time Updates
Open Source

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