BirdNet-Pi MCP Server
About
BirdNet-Pi MCP Server is a Python-based Model Context Protocol server that integrates with BirdNet-Pi to provide bird detection data retrieval, statistics, audio recording access, and report generation. It is designed for users who want to programmatically access BirdNet‑Pi…
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- Bird detection data retrieval with date and species filtering
- Detection statistics and analysis
- Audio recording access
- Daily activity patterns
- Report generation (HTML or JSON)
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
BirdNet-Pi MCP ServerCommand (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
Install dependencies from requirements.txt, set environment variables for the detection file, audio, and report directories, and run python server.py to start the server on http://localhost:8000. Use the /functions endpoint to list available functions and /invoke to call functions such as getBirdDetections and generateDetectionReport.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"birdnet-pi mcp server": {
"DMontgomery40_mcp-local-server": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}
}McpServers
{
"DMontgomery40_mcp-local-server": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}BirdNet-Pi MCP Server
A Python-based Model Context Protocol (MCP) server for BirdNet-Pi integration.
Features
- Bird detection data retrieval with date and species filtering
- Detection statistics and analysis
- Audio recording access
- Daily activity patterns
- Report generation
Requirements
- Python 3.8+
- FastAPI
- Uvicorn
- Other dependencies listed in requirements.txt
Installation
1. Clone the repository:
git clone https://github.com/YourUsername/mcp-server.git
cd mcp-server
2. Create a virtual environment and activate it:
python -m venv venv
source venv/bin/activate # On Windows use: venv\Scripts\activate
3. Install dependencies:
pip install -r requirements.txt
4. Set up your data directories:
mkdir -p data/audio data/reports
Configuration
The server can be configured using environment variables:
- BIRDNET_DETECTIONS_FILE: Path to detections JSON file (default: 'data/detections.json')
- BIRDNET_AUDIO_DIR: Path to audio files directory (default: 'data/audio')
- BIRDNET_REPORT_DIR: Path to reports directory (default: 'data/reports')
Running the Server
Start the server:
python server.py
The server will run on http://localhost:8000.
API Endpoints
- /functions - List available functions (GET)
- /invoke - Invoke a function (POST)
Available Functions
1. getBirdDetections
- Get bird detections filtered by date range and species
- Parameters: startDate, endDate, species (optional)
2. getDetectionStats
- Get detection statistics for a time period
- Parameters: period ('day', 'week', 'month', 'all'), minConfidence (optional)
3. getAudioRecording
- Get audio recording for a detection
- Parameters: filename, format ('base64' or 'buffer')
4. getDailyActivity
- Get bird activity patterns for a specific day
- Parameters: date, species (optional)
5. generateDetectionReport
- Generate a report of detections
- Parameters: startDate, endDate, format ('html' or 'json')
Directory Structure
mcp-server/
├── birdnet/
│ ├── __init__.py
│ ├── config.py
│ ├── functions.py
│ └── utils.py
├── data/
│ ├── audio/
│ └── reports/
├── server.py
├── requirements.txt
└── README.md
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