Eventor API Client
Description
# Eventor API Client A Python client for integrating with the Eventor orienteering API, providing access to events, entries, and results. ## Features - Access to event results, entries, and organization data - Configurable caching system for reduced API calls - MCP (Model…
About
# Eventor API Client A Python client for integrating with the Eventor orienteering API, providing access to events, entries, and results. ## Features - Access to event results, entries, and organization data - Configurable caching system for reduced API calls - MCP (Model Context Protocol) server integration for AI…
Details
- Author
- grapatin
- GitHub stars
- 1
- Downloads
- 292
- Categories
- Developer Tools
Jump to
- Access event results, entries, and organization data
- Configurable caching reduces API calls
- Exposes three MCP tools for AI assistants
- Parses data into LLM-friendly format
- Debug mode generates standalone JSON output
- Uses configurable API key and personId for secure access
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Eventor API ClientCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Clone the repository, set up a virtual environment with uv, install dependencies from requirements.txt, and copy the example config file to eventor_config.py. Edit that file with your actual API key and personId. To test, run python -m eventor in debug mode, which produces a JSON file. For use with Claude, add an MCP server entry to claude_desktop_config.json pointing uv at the project directory and running mcp_server.py.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"eventor api client": {
"eventor-mcp-server": {
"command": "uv",
"args": [
"venv",
".venv"
]
}
}
}
}McpServers
{
"eventor-mcp-server": {
"command": "uv",
"args": [
"venv",
".venv"
]
}
}Eventor API Client
A Python client for integrating with the Eventor orienteering API, providing access to events, entries, and results.
Features
- Access to event results, entries, and organization data
- Configurable caching system for reduced API calls
- MCP (Model Context Protocol) server integration for AI assistants
- Exposes 3 tools for MCP server:
- get_weekly_club_results() Fetches weekly club results can be used to have the LLM to summarize the results and create a report
- get_personal_events() Fetches personal events for a given personId (config file) and given period of time
- get_detailed_result_for_event_and_person() Fetches detailed results for a specific event and personId (config file)
- It does some parsing and tries to provide the data in a LLM friendly format
- Debug mode to run the client standalone and generate JSON output for review
- Configurable API key and personId for secure access
Installation
1. Clone the repository:
git clone https://github.com/grapatin/eventor-mcp-server.git
cd eventor-mcp-server
2. Set up a virtual environment:
uv venv .venv
source .venv/bin/activate # On Windows, use: .venv\Scripts\activate
3. Install dependencies:
uv pip install -r requirements.txt
4. Configure your API key:
```bash
cp eventor_config_example.py eventor_config.py
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