RateMySupervisor

Provides an MCP server to query RateMySupervisor data with intelligent name matching for mentors, departments, and reviews.
  • python

1

GitHub Stars

python

Language

4 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs
{
  "mcpServers": {
    "cjl196-ratemysupervisor_mcp": {
      "command": "python",
      "args": [
        "server.py"
      ]
    }
  }
}

The RateMySupervisor MCP Server provides an MCP-based interface to query mentor ratings from RateMySupervisor data. It includes smart name matching that handles Chinese names and their pinyin forms, enabling large language models or other MCP clients to retrieve mentor, department, and review information efficiently.

How to use

You connect your MCP-compatible client to this server to retrieve mentor ratings by name, list departments for a university, list mentors in a department, and fetch specific reviews. Use the available tools to search by name, browse universities and departments, and obtain detailed rating data.

Key capabilities you can leverage:

How to install

{
  "mcpServers": {
    "ratemy_supervisor": {
      "type": "stdio",
      "command": "python",
      "args": ["server.py"]
    }
  }
}

Additional notes

This server runs in MCP Stdio mode and expects a locally runnable Python environment. Ensure Python is installed and accessible in your system PATH. You can customize the server invocation if needed, but the recommended start is to run the server from its directory using the exact command shown above.

Security considerations include running the server in a trusted network environment and restricting access to MCP clients to prevent unauthorized data access. If you deploy publicly, consider adding authentication or network-level protections.

Troubleshooting and tips

If the server fails to start, confirm that Python is installed and that server.py is present in the working directory. Check that any required dependencies are installed via the project’s usual dependency management workflow.

When you cannot locate a mentor by name, try providing the department or university context to narrow results, and rely on the intelligent name matching to handle variations between Chinese names and their pinyin forms.

Available tools

search_supervisor_by_name

Fuzzy search for mentors by name with intelligent Chinese name and pinyin matching to find corresponding entries across potentially English or pinyin-form data.

get_departments_by_university

Return all departments for a specified university, enabling you to navigate the organizational structure and locate relevant mentors.

get_supervisors_by_university_and_department

List all mentors within a given university and department, helping you select a target for detailed reviews.

get_reviews

Fetch detailed reviews for a specific mentor within a university and department, including ratings and descriptions.

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