Mcp Agentis
What is Mcp Agentis
mcp-agentis is a Python framework designed for creating AI agents that utilize MCP servers as tools. It is compatible with any MCP server and model provider, allowing for flexible integration and functionality.
Use cases
Use cases for mcp-agentis include building AI assistants that can answer queries, automating workflows that require multiple agents, and integrating tools from different MCP servers to perform complex tasks.
How to use
To use mcp-agentis, install it via pip with the command ‘pip install agentis-mcp’. You can create an agent by loading a configuration file, initializing an AgentContext, and then using the Agent to run tasks asynchronously.
Key features
Key features of mcp-agentis include connectivity to MCP servers for tool access, the ability to build multi-agent workflows, a simple API for creating custom agents, flexible configuration options, support for various transport mechanisms, and management of both persistent and temporary connections.
Where to use
mcp-agentis can be used in various fields such as AI development, automation, data retrieval, and any application requiring interaction with MCP servers for enhanced functionality.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Mcp Agentis
mcp-agentis is a Python framework designed for creating AI agents that utilize MCP servers as tools. It is compatible with any MCP server and model provider, allowing for flexible integration and functionality.
Use cases
Use cases for mcp-agentis include building AI assistants that can answer queries, automating workflows that require multiple agents, and integrating tools from different MCP servers to perform complex tasks.
How to use
To use mcp-agentis, install it via pip with the command ‘pip install agentis-mcp’. You can create an agent by loading a configuration file, initializing an AgentContext, and then using the Agent to run tasks asynchronously.
Key features
Key features of mcp-agentis include connectivity to MCP servers for tool access, the ability to build multi-agent workflows, a simple API for creating custom agents, flexible configuration options, support for various transport mechanisms, and management of both persistent and temporary connections.
Where to use
mcp-agentis can be used in various fields such as AI development, automation, data retrieval, and any application requiring interaction with MCP servers for enhanced functionality.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
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
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
