AgentMake MCP: Your Gateway to Multi-Agent AI Systems

AgentMake MCP offers the simplest way to set up Modal Context Protocol (MCP) servers, powering them with the versatile agentic components from the AgentMake AI framework. This project provides the essential tools and infrastructure to create sophisticated multi-agent systems that can tackle complex tasks through collaboration and dynamic task allocation.

While AgentMake AI provides the core building blocks for creating individual AI agents, AgentMake MCP enables you to assemble and orchestrate them. Think of AgentMake AI as the factory for creating your specialized AI workers, and AgentMake MCP as the central command center where you manage your teams of agents on large-scale projects.

With AgentMake MCP, you can:

Integrate Diverse AI Tools: Don’t limit yourself to a single AI tool. Seamlessly connect AgentMake AI components with third-party AI tools using the standardized MCP interface.
Orchestrate Multiple Agents: Define and manage how different AI agents, each with unique skills, collaborate to achieve a common goal.
Build Complex Workflows: Design intricate workflows where agents delegate tasks, share information, and work in parallel to solve problems more efficiently.
Host Your Own MCP Server: Easily deploy a dedicated server for your multi-agent systems, allowing for robust integration with your applications and services.

Key Features

Easy Server Setup: Quickly deploy a fully functional MCP server with minimal configuration.
Seamless AgentMake AI Integration: Leverage the full power of AgentMake AI’s 16+ AI backends and 7 agentic components.
MCP Standards: Supports running both MCP tools and MCP prompts with AgentMake components.
Flexible Agent Orchestration: Define custom collaboration strategies and communication protocols for your agents.
Scalable and Extensible: Designed to support a growing number of agents and complex workflows.
Developer-Friendly: A clean and intuitive API for defining and managing your multi-agent systems.

Getting Started

1. Prerequisites

Python 3.8+
Familiarity with the agentic components supported by AgentMake AI.
Configure AI backends for AgentMake AI, read https://github.com/eliranwong/agentmake#ai-backends-configurations

Package agentmakemcp automatically includes the agentmake library.

2. Installation

pip install --upgrade agentmakemcp

To include support for Google’s Vertex AI, install with the [genai] extra:

pip install --upgrade agentmakemcp[genai]

3. Create a Configuration File

Create a Python file (e.g., my_mcp_server.py) and define a dictionary that configures your server. This dictionary can be named anything, as the server will automatically discover it.

Here is the structure of the configuration dictionary:

server (required): str - The name of your MCP server.
transport (optional): str - The transport protocol. Defaults to http.
port (optional): int - The server port. Defaults to 8080.
settings (required): list[dict] - A list of dictionaries, where each dictionary defines an MCP prompt or tool.

Each dictionary placed in the settings list may have the following keys and values:

name [required/optional]: str - This field is mandatory unless a tool is specified. It is a string value that serves as an identifier for a MCP prompt or tool.
description [required/optional]: str - This field is also mandatory unless a tool is specified. It is a string that provides a detailed description of a MCP prompt or tool.
agentmake [required]: str / list[dict] - This is a required field that can be either a string or a dictionary. To add a MCP prompt, a string value should be provided. Alternatively, to add a MCP tool, a dictionary should be used.

Setting up an MCP Prompt

To add an MCP prompt, provide the prompt string directly as the value for the agentmake key.

Setting up an MCP Tool

To add an MCP tool, provide a dictionary for the agentmake key. This dictionary specifies the parameters for the agentmake signature function from the AgentMake AI library (excluding the messages parameter).

For more details on the `agentmake` function parameters, see the `AgentMake AI documentation <https://github.com/eliranwong/agentmake/blob/main/docs/README.md>`_.

4. Running the Server

Run the agentmakemcp command from your terminal, passing your configuration file as an argument.

For examples

agentmakemcp examples/ask_multiple_models.py

agentmakemcp examples/different_persona.py

agentmakemcp examples/youtube_utilities.py

agentmakemcp teamwork_and_toolmate.py

Remarks:

You can run multiple AgentMake MCP servers simultaneously on different ports.
You can specify different AI backends for different tools, even on the same MCP server.

More Examples

You can find more advanced examples, such as chaining multiple agents together, in the /examples directory.

Integration with Third-Party AI Tools:

For example, to integrate AgentMake MCP servers with Gemini CLI:

agentmakemcp examples/ask_multiple_models.py

Edit .gemini/settings.json to include the following block:

{
  // add MCP servers
  "mcpServers": {
    "Ask Multiple AI Models": {
      "httpUrl": "http://127.0.0.1:8080/mcp/"
    }
  }
}

Contributing

We welcome contributions from the community! If you have an idea for a new feature, a bug fix, or an improvement to the documentation, please open an issue or submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

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