I craft unique cereal names, stories, and ridiculously cute Cereal Baby images.

MCP-Agentis
Marco de Python para crear agentes de IA que usan servidores MCP como herramientas. Compatible con cualquier servidor MCP y proveedor de modelos.
3 years
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Agentis MCP
A flexible multi-agent framework for building powerful AI agents with MCP server connectivity.
Features
- Connect to MCP servers for tool access and resource retrieval
- Build multi-agent workflows with powerful orchestration
- Simple and intuitive API for creating custom agents
- Flexible configuration system
- Support for different transport mechanisms (stdio, SSE)
- Persistent and temporary connection management
- Aggregation of multiple tool servers
Installation
pip install agentis-mcp
Quick Start
import asyncio
from agentis_mcp import Agent, AgentContext
from agentis_mcp.config import load_config
async def main():
# Load the configuration from a YAML file
config = load_config("config.yaml")
# Create an agent context
context = AgentContext(config)
# Create an agent with the context
async with Agent(context) as agent:
# Run a task with the agent
result = await agent.run("What's the weather in San Francisco?")
print(result)
asyncio.run(main())
Documentation
For detailed documentation, see the docs directory.
License
APACHE 2.0
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Reviews

user_vrzV1k0g
As a dedicated user of mcp-agentis, I am truly impressed by its capabilities. Developed by AgentisLabs, this amazing tool has significantly streamlined my workflow. If you are on the lookout for a reliable and efficient agent, mcp-agentis is definitely worth exploring. It’s a game-changer! Check it out here: https://github.com/AgentisLabs/mcp-agentis.