This BirdNet-Pi MCP server, developed by DMontgomery40, integrates BirdNet-Pi's bird detection capabilities with a FastAPI-based JSON-RPC interface. It provides functions for retrieving bird detections, detection statistics, audio recordings, and daily activity data. The server abstracts BirdNet-Pi's functionality, offering a standardized way for AI assistants to access and analyze bird detection data. By connecting AI systems with BirdNet-Pi's acoustic monitoring capabilities, this implementation enables applications such as automated bird species identification, habitat monitoring, and ecological research. It is particularly useful for ornithologists, conservationists, and citizen scientists who want to leverage AI for analyzing bird populations and behaviors.
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Highlight AIGet bird detections filtered by date range and optional species. Parameters: start_date (required): Start date in YYYY-MM-DD format, end_date (required): End date in YYYY-MM-DD format, species (optional): Species name filter (partial match, case-insensitive)
Get aggregate detection statistics for a time period. Parameters: period (required): day, week, month, or all, min_confidence (optional): Minimum confidence threshold 0.0-1.0 (default: 0.0)
Retrieve the audio recording for a specific bird detection. Parameters: filename (required): Audio filename from a detection record, format (optional): base64 (default) or buffer
Get hourly bird activity patterns for a specific day. Parameters: date (required): Date in YYYY-MM-DD format, species (optional): Species name filter
Generate a detection report for a date range. Parameters: start_date (required): Report start date, end_date (required): Report end date, format (optional): json (default) or html
