Serbian Data

PyPI - Version Python - Version License: MIT Smithery

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

pip install serbian-data-mcp

Features

Data Access

• 🔍 Search 3,400+ datasets from Serbian government (data.gov.rs)
• 📥 Download data in JSON, CSV, XML, XLSX formats
• 🇷🇸 Full Serbian language support (UTF-8)
• 🚀 Built-in rate limiting and caching

Visualization — 15+ Chart Types

• 📊 Basic charts: line, bar, pie, scatter, histogram, box plot
• 🗺️ Maps: choropleth (25 Serbian districts), bubble map, multi-layer map
• 📈 Data journalism: slope chart, waffle chart, population pyramid, sankey diagram, radar chart
• 🎯 Advanced: heatmap, treemap, gauge/donut, funnel, sparklines, animated timelines
• ✨ Special: arrow chart, dumbbell chart, lollipop chart

Storytelling & Analytics

• 📰 Infographics: big number cards, auto-generated insights, timeline ribbon, data tables
• 📊 Dashboards: multi-panel layouts with mixed chart types
• 📜 Scrollytelling: scroll-driven HTML stories with IntersectionObserver
• 📈 Forecasting: linear/exponential projections with R² and growth rates
• 🏆 Benchmarking: compare against EU averages or custom references
• 🔍 Cross-dataset analysis: correlations, outliers, rank divergences

Export & Sharing

• 🌐 HTML: styled, responsive pages with dark data-journalism aesthetic
• 🖼️ PNG/PDF: export with kaleido (graceful fallback if not installed)
• 📎 Embed: iframe embed code for websites/blogs
• 📋 JSON: raw Plotly spec for custom integration

Data Tools

• 🔧 Transformation tools: filter, group, aggregate, sort, select
• 📋 Auto-extracted insights: extremes, temporal changes, rankings, outliers
• 💬 Auto-generated narrative summaries
• 🔧 Git repository visualization and analysis

🚀 Quick Start

Install from PyPI (Recommended)

pip install serbian-data-mcp

Then add to your MCP client configuration (see Usage below).

Install from Smithery

Smithery is a registry and CLI for discovering and installing MCP servers.

# Install the Smithery CLI
npm install -g smithery@latest

# Add to Claude Desktop
smithery mcp add acailic/serbian-data-mcp --client claude

# Add to Cursor
smithery mcp add acailic/serbian-data-mcp --client cursor

# Or connect as a remote Smithery connection
smithery mcp add acailic/serbian-data-mcp --id serbian-data

Note: Requires Node.js 20+. After adding, restart your AI client for changes to take effect.

Install from Source

git clone https://github.com/acailic/serbian-data-mcp
cd serbian-data-mcp
uv sync

📖 Configuration

The server works out of the box with sensible defaults. To customize, create a config.json in your working directory (or next to the installed package):

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

See config.example.json in the source repo for all options.

🚀 Usage

Claude Desktop Configuration

{
  "mcpServers": {
    "serbian-data": {
      "command": "serbian-data-mcp"
    }
  }
}

Or if you installed from source:

{
  "mcpServers": {
    "serbian-data": {
      "command": "python",
      "args": ["-m", "serbian_data_mcp"]
    }
  }
}

Via Smithery CLI

If you installed via Smithery, the configuration is handled automatically. Just run:

# For Claude Desktop
smithery mcp add acailic/serbian-data-mcp --client claude

# For Cursor
smithery mcp add acailic/serbian-data-mcp --client cursor

Then restart your AI client. No manual config editing needed.

📊 Visualization Gallery

All charts feature a polished dark data-journalism theme with Inter font, refined hover styles, and consistent Serbian flag color palette. Three themes available: dark, light, and infographic.

Line Charts — Time Series & Trends

Bar Charts — Comparisons & Rankings

Choropleth Map — Serbian Districts

Interactive map of 25 Serbian districts with Cyrillic/Latin name resolution, available as choropleth or bubble map.

Population Pyramid — Demographics

Slope Chart — Ranking Changes

Shows how district rankings shifted between censuses (2002 → 2022), with green for gainers and red for losers.

Sankey Diagram — Budget Flows

Visualize budget flows from revenue sources through ministries to spending categories.

Radar Chart — Multi-Metric Comparison

Compare cities across population, GDP per capita, schools, hospitals, and parks on a single spider plot.

Waffle Chart — Proportional Data

"1 in 4 Serbs live in Belgrade" — each category gets a block of squares in a 10×10 grid.

Donut Charts — Sector Distribution

Infographics — Data Stories

Auto-generated single-page stories with big number cards, timeline ribbon, insights, and supporting charts.

Dashboards — Multi-Panel Views

Combine multiple chart types into a single dashboard layout with big number KPIs.

Scrollytelling — Scroll-Driven Stories

Interactive HTML stories that reveal data as the user scrolls, with IntersectionObserver animations.

Examples

Search & Visualize

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

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

# Create an advanced chart (slope chart for census changes)
slope = await mcp.call_tool("create_slope_chart", {
    "data": census_data,
    "entity_column": "district",
    "start_column": "pop_2002",
    "end_column": "pop_2022",
    "title": "Census Ranking Changes 2002→2022"
})

Forecast & Benchmark

# Forecast future GDP
forecast = await mcp.call_tool("forecast_data", {
    "data": gdp_data,
    "time_column": "year",
    "value_column": "gdp",
    "periods_ahead": 5
})

# Compare against benchmarks
comparison = await mcp.call_tool("benchmark_data", {
    "data": city_data,
    "value_column": "gdp_pc",
    "entity_column": "city",
    "benchmarks": {"EU average": 35000}
})

Create a Full Infographic

story = await mcp.call_tool("create_infographic", {
    "data": population_data,
    "title": "Srbija po Popisu 2022",
    "chart_type": "bar",
    "x_column": "district",
    "y_column": "population_2022",
    "extra_big_numbers": [
        {"number": "6.6M", "label": "Ukupno stanovnika", "color": "gold", "trend": "down"},
        {"number": "23%", "label": "Beograd region", "color": "blue", "trend": "up"},
    ],
    "timeline_events": [
        {"year": "2002", "label": "Popis 2002", "dot_class": ""},
        {"year": "2022", "label": "Popis 2022", "dot_class": "gold"},
    ]
})

Available MCP Tools

Data Access

Tool	Description
search_datasets	Search 3,400+ datasets with filters
get_dataset	Get complete dataset details
get_resource_data	Download and parse resource data
list_organizations	Browse data providers
suggest_datasets	Autocomplete for search

Data Transformation

Tool	Description
filter_data	Filter rows by conditions
group_data	Group and aggregate
sort_data	Sort by column(s)
select_columns	Select/rename columns
data_profile	Statistical summary of dataset

Basic Charts

Tool	Description
create_visualization	Line, bar, pie, scatter, histogram, box plot
create_advanced_visualization	Heatmap, treemap, gauge, funnel, sparklines, animated
create_arrow_chart	Directional arrow chart
create_dumbbell_chart	Before/after comparison

Novel Charts

Tool	Description
create_slope_chart	Ranking changes between two periods
create_waffle_chart	Proportional icon grid
create_population_pyramid	Age × sex demographic distribution
create_sankey_diagram	Budget/energy flow visualization
create_radar_chart	Multi-metric spider comparison

Maps

Tool	Description
create_choropleth_map	Colored district map of Serbia
create_bubble_map	Bubble-sized district map
create_multi_layer_map	Toggle between indicators

Analytics & Forecasting

Tool	Description
forecast_data	Linear/exponential projections
benchmark_data	Compare against reference values
compare_cross_dataset	Cross-dataset correlations

Storytelling

Tool	Description
create_infographic	Full data story with KPIs, timeline, chart, insights
create_dashboard	Multi-panel dashboard layout
create_scrollytelling	Scroll-driven interactive story

Export & Sharing

Tool	Description
export_visualization	Export as HTML, JSON, PNG, or PDF
generate_embed	Generate iframe embed code
enhance_chart_tooltips	Add rich contextual tooltips

📚 Documentation

• 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

Development

Setup Development Environment

make install

Generate Showcase Exports

uv run python generate_showcase.py

This creates 12 polished HTML files in exports/ demonstrating all chart types with sample Serbian data.

Running Tests

make test       # Run all tests with coverage
make test-quick # Quick tests (no coverage)

Code Quality Checks

make check      # Run all quality checks (lint, format, type-check, security)
make check-quick # Quick checks (lint + format only)

Project Structure

serbian-data-mcp/
├── exports/                     # Generated HTML visualizations
├── src/serbian_data_mcp/
│   ├── api/                     # API client for data.gov.rs
│   ├── catalog/                 # Dataset catalog and search
│   ├── data/                    # Data parsing and transformation
│   ├── intelligence/            # Query expansion and smart search
│   ├── viz/
│   │   ├── charts.py            # Basic 6 chart types (auto-themed)
│   │   ├── advanced_charts.py   # Heatmap, treemap, gauge, funnel, sparklines
│   │   ├── novel_charts.py      # Slope, waffle, pyramid, sankey, radar
│   │   ├── maps.py              # Choropleth map of 25 Serbian districts
│   │   ├── map_advanced.py      # Bubble map, multi-layer map
│   │   ├── infographics.py      # Full infographic builder
│   │   ├── scrollytelling.py    # Scroll-driven HTML stories
│   │   ├── animations.py        # Animated charts (timeline, bars, comparison)
│   │   ├── themes.py            # Dark/light/infographic themes
│   │   ├── insights.py         # Auto-extracted insights & narratives
│   │   ├── tooltips.py          # Rich hover tooltips
│   │   ├── forecast.py          # Linear/exponential forecasting
│   │   ├── data_tables.py        # Styled data tables
│   │   ├── special_charts.py    # Arrow, dumbbell, lollipop
│   │   ├── exporters.py         # HTML/PNG/JSON/PDF/export
│   │   └── datawrapper_export.py # Datawrapper cloud API
│   ├── config.py                # Configuration management
│   ├── exceptions.py            # Custom exceptions
│   └── tools.py                 # MCP tool definitions (30+ tools)
├── tests/                       # Comprehensive test suite (314 tests)
├── generate_showcase.py         # Generate showcase HTML exports
├── .github/workflows/           # CI/CD configuration
├── pyproject.toml               # Project configuration
└── Makefile                     # Development commands

License

MIT License - see LICENSE file