Allows users to access repository functionality, including cloning the repository and handling issues for feature requests and bug reports.
Facilitates installation and execution of the MCP plugin through NPX commands.
Enables data-driven visualizations using React artifacts for displaying bird detection data and statistics.
mcp-server-birdstats
Cross-reference your BirdNET-Pi data with eBird observations using natural language
Overview
This MCP plugin allows you to analyze BirdNET-Pi/BirdWeather detections by connecting them with eBird's extensive database.
Features
Natural language interface for querying birdnet-pi / birdweather, and eBird data
Cross-reference BirdWeather detections with eBird observations
Data-driven visualizations with React artifacts
Installation
Clone the repository:
Install dependencies:
Claude Config
Usage
The plugin processes natural language queries about your bird detection data. Example queries:
"My BirdNET heard a Swainson's Thrush - is that unusual?"
"What's my station's rarest detection this week?"
"Graph my detections by time of day"
"Are others seeing these warblers on eBird?"
Data Integrity
This plugin strictly adheres to data integrity principles:
Only uses actual API response data
Never creates example or estimated data
Always shows observation counts with percentages
Clear indication when data is unavailable
Core Logic
The core functionality is contained in a single text file under src/index.txt
which includes:
BirdWeather API interactions
eBird API interactions
Data analysis functions
Type definitions
Helper utilities
API Integration
BirdWeather API
Station statistics
Species lists
Detection records
eBird API
Recent observations
Notable sightings
Hotspot data
Species information
License
MIT
Support
For issues and feature requests, please open an issue on the GitHub repository.
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Cross-reference your BirdNET-Pi data with eBird observations using natural language
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