Serbian Data MCP Server

MCP server for accessing Serbian open data portal (data.gov.rs) with built-in visualization capabilities.

Features

• 🔍 Search 3,400+ datasets from Serbian government

• 📊 Create 6 types of charts (line, bar, pie, scatter, histogram, box)

• 📥 Download data in JSON, CSV, XML, XLSX formats

• 🎨 Export visualizations as HTML/PNG/JSON

• 🇷🇸 Full Serbian language support (UTF-8)

• 🚀 Built-in rate limiting and caching

• 📖 Comprehensive documentation with 24+ examples

• 🛠️ Data transformation tools (filter, group, aggregate, sort, select)

Related MCP server: Berlin Open Data MCP Server

🚀 Quick Start

Option 1: Automated Setup (Recommended)

# Run the interactive setup wizard
./setup.sh

This will automatically:

• ✅ Check your Python installation

• ✅ Create configuration with sensible defaults

• ✅ Install all dependencies

• ✅ Set up necessary directories

• ✅ Test the installation

Option 2: Manual Setup

# Clone repository
git clone https://github.com/acailic/serbian-data-mcp
cd serbian-data-mcp

# Install with uv
uv sync

# Or with pip
pip install -e .

# Create configuration
cp config.example.json config.json

📖 Configuration

Interactive Configuration Wizard

python configure.py

The wizard guides you through:

• API settings (URL, rate limiting, timeout)

• Directory preferences (cache, exports)

• Validation with helpful error messages

• Automatic directory creation

Manual Configuration

Edit config.json (created from config.example.json):

{
  "api_base": "https://data.gov.rs",
  "rate_limit": 1.0,
  "timeout": 30,
  "cache_dir": ".cache",
  "export_dir": "exports"
}

🧪 Testing

Test API Connection

./test_connection.sh

This validates:

• Connectivity to data.gov.rs

• API response format

• Available dataset count

Run Examples

python example_usage.py

Demonstrates:

• Dataset search

• Data retrieval

• Visualization creation

• Export functionality

📚 Documentation

📖 Complete Documentation Available in docs/

• Quick Start Guide - Get started in 5 minutes

• Usage Examples - 24+ real-world examples and use cases

• API Reference - Complete tool documentation with parameters

• Troubleshooting - Common issues and solutions

• Contributing Guide - Developer contribution guidelines

• docs/README.md - Documentation navigation and index

Additional Resources:

• DEV_GUIDE.md - Comprehensive developer guide

• Examples - Check example_usage.py for usage patterns

• Error Handling - Helpful error messages for common issues

🚀 Usage

Claude Desktop Configuration

Add to Claude Desktop config:

{
  "mcpServers": {
    "serbian-data": {
      "command": "uv",
      "args": ["--directory", "/path/to/serbian-data-mcp", "run", "python", "-m", "serbian_data_mcp"]
    }
  }
}

Available Tools

• search_datasets - Search datasets with filters

• get_dataset - Get complete dataset details

• get_resource_data - Download and parse resource data

• create_visualization - Create charts from data

• list_organizations - Browse data providers

• suggest_datasets - Autocomplete for search

Examples

# Search datasets
datasets = await mcp.call_tool("search_datasets", {
    "query": "population",
    "format": "json",
    "page_size": 10
})

# Create visualization
chart = await mcp.call_tool("create_visualization", {
    "data": data,
    "chart_type": "line",
    "title": "Population Trends",
    "x_column": "year",
    "y_column": "population",
    "export_format": "html"
})

Development

Setup Development Environment

# Install dependencies
make install

# Or manually
uv sync --dev

Running Tests

# Run all tests with coverage
make test

# Quick tests (no coverage)
make test-quick

# Only unit tests
make test-unit

# Only integration tests
make test-integration

Code Quality Checks

# Run all quality checks (lint, format, type-check, security)
make check

# Quick checks (lint + format only)
make check-quick

# Individual checks
make lint      # Ruff linting
make format    # Format code with ruff
make type-check # Type checking with pyright
make security  # Security checks with bandit

Available Make Commands

make help      # Show all available commands
make install   # Install dependencies
make test      # Run tests with coverage
make check     # Run all quality checks
make clean     # Clean up generated files
make dev       # Setup development environment
make all       # Install, test, and check

Testing Infrastructure

The project includes comprehensive testing infrastructure:

• Unit Tests: Individual component testing

• Integration Tests: End-to-end workflow testing

• Coverage Reports: HTML and terminal coverage output

• Type Checking: 100% type coverage with pyright

• Code Quality: Automated linting and formatting with ruff

• Security Checks: Bandit security scanning

CI/CD Pipeline

GitHub Actions workflows automatically run:

1. Test Suite (.github/workflows/test.yml)

   • Tests on Python 3.11, 3.12, 3.13

   • Coverage reporting to Codecov

2. Code Quality (.github/workflows/code-quality.yml)

   • Type checking with pyright

   • Linting with ruff

   • Formatting checks

   • Security scanning with bandit

Project Structure

serbian-data-mcp/
├── src/serbian_data_mcp/
│   ├── api/              # API client and models
│   ├── data/             # Data parsing and transformation
│   ├── viz/              # Visualization tools
│   └── config.py         # Configuration management
├── tests/                # Comprehensive test suite
├── .github/workflows/    # CI/CD configuration
├── pyproject.toml        # Project configuration
└── Makefile              # Development commands

Quality Standards

• Type Coverage: 100% (strict pyright checking)

• Test Coverage: Comprehensive with coverage reporting

• Code Style: Automated formatting with ruff (120 char line length)

• Security: Automated security scanning

• CI/CD: Automated testing on multiple Python versions

License

MIT License - see LICENSE file