mcp-local-server
Language:
Python
Stars:
3
Forks:
1
README
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
-
Clone the repository:
git clone https://github.com/YourUsername/mcp-server.git cd mcp-server -
Create a virtual environment and activate it:
python -m venv venv source venv/bin/activate # On Windows use: venv\Scripts\activate -
Install dependencies:
pip install -r requirements.txt -
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
-
getBirdDetections- Get bird detections filtered by date range and species
- Parameters: startDate, endDate, species (optional)
-
getDetectionStats- Get detection statistics for a time period
- Parameters: period ('day', 'week', 'month', 'all'), minConfidence (optional)
-
getAudioRecording- Get audio recording for a detection
- Parameters: filename, format ('base64' or 'buffer')
-
getDailyActivity- Get bird activity patterns for a specific day
- Parameters: date, species (optional)
-
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 Publisher info
DMontgomery40
Cybersecurity researcher and open source advocate and developer. Passionately supporting open source solutions to the cross section of AI and Security.
More MCP servers built with Python
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.