by isakskogstad
Kolada — Explore Swedish municipality and regional statistics, KPIs and comparisons for all 290 municipalities and 21 re
Provides access to over 5,000 KPIs and statistics for all 290 Swedish municipalities and 21 regions through the Kolada open data API.
Kolada is a community-built MCP server published by isakskogstad that provides AI assistants with tools and capabilities via the Model Context Protocol. Kolada — Explore Swedish municipality and regional statistics, KPIs and comparisons for all 290 municipalities and 21 re It is categorized under developer tools, analytics data. This server exposes 21 tools that AI clients can invoke during conversations and coding sessions.
You can install Kolada in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
MIT
Kolada is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
Kolada is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, Kolada benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
I recommend Kolada for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We evaluated Kolada against two servers with overlapping tools; this profile had the clearer scope statement.
We evaluated Kolada against two servers with overlapping tools; this profile had the clearer scope statement.
I recommend Kolada for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Kolada reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We wired Kolada into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Kolada is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Strong directory entry: Kolada surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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Kolada — Explore Swedish municipality and regional statistics, KPIs and comparisons for all 290 municipalities and 21 re
TL;DR: Provides access to over 5,000 KPIs and statistics for all 290 Swedish municipalities and 21 regions through the Kolada open data API.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
