https://github.com/eliranwong/agentmakemcp
https://github.com/eliranwong/agentmakemcp
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/eliranwong/agentmakemcp
- Owner: eliranwong
- License: mit
- Created: 2025-08-18T20:28:39.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2025-09-06T19:38:54.000Z (about 1 month ago)
- Last Synced: 2025-09-06T21:32:06.725Z (about 1 month ago)
- Language: Python
- Size: 43.9 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# AgentMake MCP: Your Gateway to Multi-Agent AI Systems
[](https://badge.fury.io/py/agentmakemcp)
[](https://opensource.org/licenses/MIT)
**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.
## Table of Contents
- [AgentMake MCP: Your Gateway to Multi-Agent AI Systems](#agentmake-mcp-your-gateway-to-multi-agent-ai-systems)
- [Table of Contents](#table-of-contents)
- [How it Works](#how-it-works)
- [Key Features](#key-features)
- [Getting Started](#getting-started)
- [1. Prerequisites](#1-prerequisites)
- [2. Installation](#2-installation)
- [3. Create a Configuration File](#3-create-a-configuration-file)
- [4. Running the Server](#4-running-the-server)
- [Usage](#usage)
- [Integrating with Third-Party AI Tools](#integrating-with-third-party-ai-tools)
- [Examples](#examples)
- [Contributing](#contributing)
- [License](#license)
## How it Works
The following diagram illustrates the relationship between `AgentMake AI`, `AgentMake MCP`, and a third-party AI tool (in this case, `Gemini CLI`):
```mermaid
graph TD
subgraph "Third-Party AI Tool (e.g., Gemini CLI)"
A[User] --> B{Gemini CLI};
end
subgraph "AgentMake MCP Server"
C[agentmakemcp] --> D{MCP Server};
end
subgraph "AgentMake AI"
E[agentmake] --> F[AI Backends];
end
B -->|MCP Request| D;
D -->|AgentMake Request| E;
E -->|API Request| F;
F -->|API Response| E;
E -->|AgentMake Response| D;
D -->|MCP Response| B;
```
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
```bash
pip install --upgrade agentmakemcp
```
To include support for Google's Vertex AI, install with the `[genai]` extra:
```bash
pip install --upgrade agentmakemcp[genai]
```
### 3. Create a Configuration File
Create a Python file (e.g., `examples/ask_multiple_models.py`) and define a dictionary that configures your server.
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).*
#### Full Configuration Examples
Full configuration examples can be found in https://github.com/eliranwong/agentmakemcp/tree/main/examples
### 4. Running the Server
Run the `agentmakemcp` command from your terminal, passing your configuration file as an argument.
```bash
agentmakemcp examples/ask_multiple_models.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.
## Usage
Once your MCP server is running, you can integrate it with any third-party AI tool that supports the Modal Context Protocol.
### Integrating with Third-Party AI Tools
For example, to integrate `AgentMake MCP servers` with `Gemini CLI`:
First, start your MCP server, e.g. run the configuration file `ask_multiple_models.py` in the directory `examples`:
```bash
agentmakemcp examples/ask_multiple_models.py
```
Then, edit your `.gemini/settings.json` to include the following block:
```json
{
// add MCP servers
"mcpServers": {
"Ask Multiple AI Models": {
"httpUrl": "http://127.0.0.1:8080/mcp/"
}
}
}
```
Now, you can use the tools and prompts defined in your MCP server from within Gemini CLI.
## Examples
You can find more advanced examples in the [`/examples`](https://github.com/eliranwong/agentmakemcp/tree/main/examples) directory.
* [ask_multiple_models.py](https://github.com/eliranwong/agentmakemcp/blob/main/examples/ask_multiple_models.py)
* [different_persona.py](https://github.com/eliranwong/agentmakemcp/blob/main/examples/different_persona.py)
* [teamwork_and_toolmate.py](https://github.com/eliranwong/agentmakemcp/blob/main/examples/teamwork_and_toolmate.py)
* [youtube_utilities.py](https://github.com/eliranwong/agentmakemcp/blob/main/examples/youtube_utilities.py)
To run an example:
```bash
agentmakemcp examples/ask_multiple_models.py
```
## 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/agentmakemcp/blob/main/LICENSE) for details.