Emeritus Server
БесплатноНе проверенMCP server for integrating AI models with Emeritus services, enabling user management, tag operations, order management, and leads import via a standardized int
Описание
MCP server for integrating AI models with Emeritus services, enabling user management, tag operations, order management, and leads import via a standardized interface.
README
This project is a Model Context Protocol (MCP) server implementation for the Emeritus API. It provides a standardized interface for AI models to interact with Emeritus services, including user management, tag operations, order management, and leads import.
About Model Context Protocol (MCP)
The Model Context Protocol (MCP) is an open standard introduced by Anthropic that enables seamless integration between LLM applications and external data sources and tools. Think of MCP as a "USB-C for AI applications" - it provides a standardized way to connect AI models with external systems.
MCP uses a client-server architecture where:
- MCP Servers expose capabilities (tools, resources, prompts) in a standardized way
- MCP Clients (within AI applications) connect to these servers
- JSON-RPC 2.0 is used for communication between clients and servers
Features
This MCP server provides:
- Tools: Functions that AI models can execute to interact with Emeritus services
- User management (create, fetch, update users)
- Tag operations (create groups, assign tags)
- Order management (fetch orders and financial records)
- Leads import functionality
- Resources: Access to Emeritus data sources
- Secure Authentication: Token-based authentication with the Emeritus API
- Error Handling: Comprehensive error reporting and validation
Requirements
- Python 3.10 or higher
- Access to Emeritus API credentials
- An MCP-compatible client (like Claude Desktop, or any application using MCP SDKs)
Installation
- Clone the repository:
git clone <repository-url>
cd emeritus-mcp
- Create a virtual environment and install dependencies:
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
pip install -e .
- Create a
.envfile based on the provided.env.example:
cp .env.example .env
- Edit the
.envfile with your Emeritus API credentials.
Configuration
Set the following environment variables in the .env file:
EMERITUS_API_HOST: The Emeritus API host URLEMERITUS_USER_ID: Your Emeritus User IDEMERITUS_API_SECRET: Your Emeritus API SecretDEBUG: Set toTruefor development,Falsefor production
Usage
Running the MCP Server
Start the server using the MCP standard way:
python -m emeritus_mcp
Or run directly:
python src/emeritus_mcp/server.py
Connecting to the Server
This MCP server can be used with any MCP-compatible client. For example:
Claude Desktop
Add the server to your Claude Desktop configuration:
{
"mcpServers": {
"emeritus": {
"command": "python",
"args": ["-m", "emeritus_mcp"],
"env": {
"EMERITUS_API_HOST": "your-api-host",
"EMERITUS_USER_ID": "your-user-id",
"EMERITUS_API_SECRET": "your-secret"
}
}
}
}
Other MCP Clients
Use the standard MCP connection protocols (stdio, SSE) supported by your client.
Available Tools
The server exposes the following tools that AI models can use:
User Management
create_user: Create a user by mobile number or emailfetch_user_profile: Get a user's profile informationupdate_user_owner: Update a user's ownerupdate_user_pool: Update a user's poolupdate_user_email: Update a user's emailfetch_user_contact: Fetch a user's contact information
Tag Management
create_tag_group: Create a tag grouplist_tag_groups: Get a list of tag groupsupdate_tag_group: Update a tag groupdeactivate_tag_group: Deactivate a tag groupactivate_tag_group: Activate a tag groupassign_user_tag: Assign a tag to a userlist_user_tags: List tags assigned to a user
Order Management
fetch_order: Get details for a specific orderlist_orders: Get a list of orderslist_order_financials: Get a list of order financial records
Leads Management
import_leads: Import leads from raw data
Project Structure
emeritus-mcp/
├── pyproject.toml # Project dependencies and configuration
├── README.md # Project documentation
├── .env.example # Example environment variables
├── src/
│ └── emeritus_mcp/ # Main package
│ ├── __init__.py # Package initialization
│ ├── __main__.py # CLI entry point
│ ├── server.py # MCP server implementation
│ ├── tools/ # MCP tools implementation
│ │ ├── __init__.py
│ │ ├── user.py # User management tools
│ │ ├── tag.py # Tag management tools
│ │ ├── order.py # Order management tools
│ │ └── leads.py # Leads management tools
│ ├── services/ # Emeritus API integration
│ │ ├── __init__.py
│ │ └── emeritus_client.py
│ └── config/ # Configuration management
│ ├── __init__.py
│ └── settings.py
Development
Testing
Run tests with pytest:
pytest
Code Formatting
Format code with Black and isort:
black src tests
isort src tests
Type Checking
Run type checking with mypy:
mypy src
Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Ensure all tests pass
- Submit a pull request
License
This project is licensed under the MIT License - see the LICENSE file for details.
More About MCP
To learn more about the Model Context Protocol:
Установка Emeritus Server
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/Emeritus-China/emeritus-mcpFAQ
Emeritus Server MCP бесплатный?
Да, Emeritus Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Emeritus Server?
Нет, Emeritus Server работает без API-ключей и переменных окружения.
Emeritus Server — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить Emeritus Server в Claude Desktop, Claude Code или Cursor?
Открой Emeritus Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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