Emeritus MCP Server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Emeritus MCP ServerFetch the profile of user with ID 12345"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Emeritus MCP Server
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
Related MCP server: MCP-Saptiva
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-mcpCreate 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 .envEdit 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_mcpOr run directly:
python src/emeritus_mcp/server.pyConnecting 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.pyDevelopment
Testing
Run tests with pytest:
pytestCode Formatting
Format code with Black and isort:
black src tests
isort src testsType Checking
Run type checking with mypy:
mypy srcContributing
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:
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