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    Kolada Mcp

    An MCP server for Kolada.

    13 stars
    Python
    Updated Jul 29, 2025

    Table of Contents

    • Overview
    • Features
    • Available Tools
    • Installation
    • Using pip
    • Using Docker
    • Usage
    • Stdio Mode (Default)
    • HTTP Mode
    • Claude Desktop Integration
    • Configuration
    • Development
    • Setup
    • Running Tests
    • Code Quality
    • Architecture
    • License

    Table of Contents

    • Overview
    • Features
    • Available Tools
    • Installation
    • Using pip
    • Using Docker
    • Usage
    • Stdio Mode (Default)
    • HTTP Mode
    • Claude Desktop Integration
    • Configuration
    • Development
    • Setup
    • Running Tests
    • Code Quality
    • Architecture
    • License

    Documentation

    Kolada MCP Server

    A clean, standalone MCP (Model Context Protocol) server for Sweden's Kolada municipal statistics API.

    Overview

    This server provides AI applications with access to Sweden's comprehensive municipal and regional statistics database. It enables natural language queries against thousands of Key Performance Indicators (KPIs) covering various aspects of Swedish public sector data.

    Features

    • 9 MCP Tools for comprehensive data access
    • Semantic Search using Swedish BERT embeddings
    • No External Dependencies - fully standalone (no Mima or Redis)
    • Containerized with Docker support
    • Modern Python 3.11+ with type hints and async/await

    Available Tools

    ToolDescription
    list_operating_areasList all KPI categories with counts
    get_kpis_by_operating_areaGet KPIs within a specific category
    search_kpisSemantic search for KPIs using natural language
    get_kpi_metadataGet detailed metadata for a specific KPI
    fetch_kolada_dataFetch raw KPI data for municipalities
    analyze_kpi_across_municipalitiesComparative analysis with rankings
    compare_kpisCompare two KPIs (difference or correlation)
    list_municipalitiesList municipalities/regions
    filter_municipalities_by_kpiFilter by KPI threshold

    Installation

    Using pip

    bash
    pip install -e .

    Using Docker

    bash
    docker-compose up -d kolada-mcp

    Usage

    Stdio Mode (Default)

    bash
    kolada-mcp
    # or
    python -m kolada_mcp

    HTTP Mode

    bash
    MCP_TRANSPORT=http PORT=8001 kolada-mcp

    Claude Desktop Integration

    Add to your Claude Desktop configuration:

    json
    {
      "mcpServers": {
        "kolada": {
          "command": "kolada-mcp"
        }
      }
    }

    Configuration

    Environment variables:

    VariableDefaultDescription
    MCP_TRANSPORTstdioTransport mode (stdio or http)
    PORT8001HTTP server port
    LOG_LEVELINFOLogging level

    Development

    Setup

    bash
    # Create virtual environment
    python -m venv .venv
    source .venv/bin/activate
    
    # Install with dev dependencies
    pip install -e ".[dev]"

    Running Tests

    bash
    pytest

    Code Quality

    bash
    # Linting
    ruff check src tests
    
    # Type checking
    mypy src

    Architecture

    code
    src/kolada_mcp/
    ├── __init__.py          # Package init
    ├── __main__.py          # Entry point
    ├── config.py            # Settings (Pydantic)
    ├── server.py            # FastMCP server
    ├── models/
    │   └── types.py         # Data models
    ├── services/
    │   ├── kolada_client.py # API client
    │   ├── embeddings.py    # Semantic search
    │   └── data_processing.py
    └── tools/
        ├── metadata.py      # KPI metadata tools
        ├── data.py          # Data fetching tools
        ├── municipality.py  # Municipality tools
        └── comparison.py    # Comparison tools

    License

    Apache-2.0

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