=========================================================
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 <https://github.com/eliranwong/agentmake>`_ 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 <https://github.com/eliranwong/agentmake>`_.
* Configure AI backends for `AgentMake AI`, read https://github.com/eliranwong/agentmake#ai-backends-configurations
Package `agentmakemcp` automatically includes the `agentmake` library.
2. Installation
---------------
.. code-block:: bash
pip install --upgrade agentmakemcp
To include support for Google's Vertex AI, install with the `[genai]` extra:
.. code-block:: bash
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**
.. code-block:: bash
agentmakemcp examples/ask_multiple_models.py
.. code-block:: bash
agentmakemcp examples/different_persona.py
.. code-block:: bash
agentmakemcp examples/youtube_utilities.py
.. code-block:: bash
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 <https://github.com/eliranwong/agentmake_mcp/tree/main/examples>`_ directory.
Integration with Third-Party AI Tools:
========================================
For example, to integrate `AgentMake MCP servers` with `Gemini CLI`:
.. code-block:: bash
agentmakemcp examples/ask_multiple_models.py
Edit `.gemini/settings.json` to include the following block:
.. code-block:: json
{
// 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 <https://github.com/eliranwong/agentmake_mcp/blob/main/LICENSE>`_ for details.
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"description": "=========================================================\nAgentMake MCP: Your Gateway to Multi-Agent AI Systems\n=========================================================\n\n**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 <https://github.com/eliranwong/agentmake>`_ 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.\n\nWhile **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.\n\nWith AgentMake MCP, you can:\n\n* **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.\n* **Orchestrate Multiple Agents:** Define and manage how different AI agents, each with unique skills, collaborate to achieve a common goal.\n* **Build Complex Workflows:** Design intricate workflows where agents delegate tasks, share information, and work in parallel to solve problems more efficiently.\n* **Host Your Own MCP Server:** Easily deploy a dedicated server for your multi-agent systems, allowing for robust integration with your applications and services.\n\nKey Features\n============\n\n* **Easy Server Setup:** Quickly deploy a fully functional MCP server with minimal configuration.\n* **Seamless AgentMake AI Integration:** Leverage the full power of AgentMake AI's 16+ AI backends and 7 agentic components.\n* **MCP Standards:** Supports running both MCP tools and MCP prompts with `AgentMake` components.\n* **Flexible Agent Orchestration:** Define custom collaboration strategies and communication protocols for your agents.\n* **Scalable and Extensible:** Designed to support a growing number of agents and complex workflows.\n* **Developer-Friendly:** A clean and intuitive API for defining and managing your multi-agent systems.\n\nGetting Started\n===============\n\n1. Prerequisites\n----------------\n\n* Python 3.8+\n* Familiarity with the agentic components supported by `AgentMake AI <https://github.com/eliranwong/agentmake>`_.\n* Configure AI backends for `AgentMake AI`, read https://github.com/eliranwong/agentmake#ai-backends-configurations\n\nPackage `agentmakemcp` automatically includes the `agentmake` library.\n\n2. Installation\n---------------\n\n.. code-block:: bash\n\n pip install --upgrade agentmakemcp\n\nTo include support for Google's Vertex AI, install with the `[genai]` extra:\n\n.. code-block:: bash\n\n pip install --upgrade agentmakemcp[genai]\n\n3. Create a Configuration File\n------------------------------\n\nCreate 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.\n\nHere is the structure of the configuration dictionary:\n\n* `server` (required): `str` - The name of your MCP server.\n* `transport` (optional): `str` - The transport protocol. Defaults to `http`.\n* `port` (optional): `int` - The server port. Defaults to `8080`.\n* `settings` (required): `list[dict]` - A list of dictionaries, where each dictionary defines an MCP prompt or tool.\n\nEach dictionary placed in the settings list may have the following keys and values:\n\n* `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.\n* `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.\n* `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.\n\nSetting up an MCP Prompt\n~~~~~~~~~~~~~~~~~~~~~~~~\n\nTo add an MCP prompt, provide the prompt string directly as the value for the `agentmake` key.\n\nSetting up an MCP Tool\n~~~~~~~~~~~~~~~~~~~~~~\n\nTo 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).\n\n*For more details on the `agentmake` function parameters, see the `AgentMake AI documentation <https://github.com/eliranwong/agentmake/blob/main/docs/README.md>`_.*\n\n4. Running the Server\n---------------------\n\nRun the `agentmakemcp` command from your terminal, passing your configuration file as an argument.\n\n**For examples**\n\n.. code-block:: bash\n\n agentmakemcp examples/ask_multiple_models.py\n\n.. code-block:: bash\n\n agentmakemcp examples/different_persona.py\n\n.. code-block:: bash\n\n agentmakemcp examples/youtube_utilities.py\n\n.. code-block:: bash\n\n agentmakemcp teamwork_and_toolmate.py\n\n**Remarks:**\n\n* You can run multiple AgentMake MCP servers simultaneously on different ports.\n* You can specify different AI backends for different tools, even on the same MCP server.\n\nMore Examples\n=============\n\nYou can find more advanced examples, such as chaining multiple agents together, in the `/examples <https://github.com/eliranwong/agentmake_mcp/tree/main/examples>`_ directory.\n\nIntegration with Third-Party AI Tools:\n========================================\n\nFor example, to integrate `AgentMake MCP servers` with `Gemini CLI`:\n\n.. code-block:: bash\n\n agentmakemcp examples/ask_multiple_models.py\n\nEdit `.gemini/settings.json` to include the following block:\n\n.. code-block:: json\n\n {\n // add MCP servers\n \"mcpServers\": {\n \"Ask Multiple AI Models\": {\n \"httpUrl\": \"http://127.0.0.1:8080/mcp/\"\n }\n }\n }\n\nContributing\n============\n\nWe 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.\n\nLicense\n=======\n\nThis project is licensed under the MIT License. See the `LICENSE file <https://github.com/eliranwong/agentmake_mcp/blob/main/LICENSE>`_ for details.\n",
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