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Mcp Dst
What is Mcp Dst
mcp-dst is an MCP server that exposes the Danmarks Statistik Statistikbank API as programmable resources, facilitating integration with language models and modern AI applications.
Use cases
Typical use cases include asking questions like ‘How many people live in Copenhagen?’ or ‘Which municipality has had the largest percentage decrease in population over the last 10 years?’.
How to use
Users can interact with the MCP server by asking questions in Danish. The AI assistant will automatically find relevant tables and data, presenting results in an understandable manner without requiring coding skills.
Key features
Full access to Danmarks Statistik API endpoints, support for all original API parameters, data returned in various formats (JSON, JSONSTAT, CSV, etc.), and suitability for integration with Large Language Models (LLMs) that support MCP.
Where to use
mcp-dst can be used in fields such as data analysis, AI-assisted research, and applications requiring statistical data from Danmarks Statistik.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Mcp Dst
mcp-dst is an MCP server that exposes the Danmarks Statistik Statistikbank API as programmable resources, facilitating integration with language models and modern AI applications.
Use cases
Typical use cases include asking questions like ‘How many people live in Copenhagen?’ or ‘Which municipality has had the largest percentage decrease in population over the last 10 years?’.
How to use
Users can interact with the MCP server by asking questions in Danish. The AI assistant will automatically find relevant tables and data, presenting results in an understandable manner without requiring coding skills.
Key features
Full access to Danmarks Statistik API endpoints, support for all original API parameters, data returned in various formats (JSON, JSONSTAT, CSV, etc.), and suitability for integration with Large Language Models (LLMs) that support MCP.
Where to use
mcp-dst can be used in fields such as data analysis, AI-assisted research, and applications requiring statistical data from Danmarks Statistik.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
MCP Server for Danmarks Statistik
En MCP server, der eksponerer Danmarks Statistiks Statistikbank API som programmerbare ressourcer, hvilket gør det nemt at integrere med sprogmodeller og moderne AI-applikationer.
Funktioner
- Fuld adgang til Danmarks Statistik API endpoints:
- Emner (subjects)
- Tabeller (tables)
- Tabelmetadata (tableinfo)
- Data
- Understøtter alle originale parametre fra API’et
- Returnerer data i forskellige formater: JSON, JSONSTAT, CSV, m.fl.
- Velegnet til integration med Large Language Models (LLMs) der understøtter MCP
Værdi og anvendelse
Denne MCP-integration giver mulighed for at bygge AI-assistenter, der kan udføre datadrevne analyser baseret på naturlig sproginteraktion med Danmarks Statistiks data. Brugerne kan stille almindelige spørgsmål på dansk, og AI-assistenten finder selv de relevante tabeller, henter data, og præsenterer resultaterne på en forståelig måde.
Konkrete eksempler på spørgsmål
Med denne integration kan brugere stille simple spørgsmål som:
- “Hvor mange mennesker bor der i København?” (667.099 indbyggere iflg. seneste tal)
- “Hvilken kommune har de sidste 10 år haft det største procentvise fald i indbyggere?” (Lolland med et fald på 9,07%)
- “I hvilken kommune bor flest i almen boligbyggeri?” (absolut: København, procentvis: Brøndby med 50,9%)
- “Hvordan er kønsfordelingen blandt beboere i almene boliger?” (53,3% kvinder / 46,7% mænd nationalt)
Fordele
- Ingen kodekundskaber krævet - Slutbrugeren behøver ikke kende til SQL, programmering eller datastrukturer
- Naturligt sprog - Interaktion foregår med almindelige spørgsmål på dansk
- Automatisk datafinding - AI-assistenten finder selv de relevante tabeller og data
- Kontekstbevidst analyse - Kan sammenligne data på tværs af tid, geografi og kategorier
- Tidsbesparende - Eliminerer behovet for manuel datasøgning og -behandling
- Demokratiserer data - Gør komplekse statistiske data tilgængelige for alle

Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










