SSB-MCP

Overview

Ssb Mcp is a dedicated MCP server that bridges AI assistants with the Statistics Norway (SSB) API, enabling agents to pull and manipulate Norwegian statistical data without leaving their native conversational environment. By exposing SSB’s extensive datasets through a single, well‑defined MCP interface, the server eliminates the need for developers to write custom adapters or manage authentication flows manually. This makes it straightforward to embed up‑to‑date demographic, economic, and social statistics into AI workflows.

The server offers a standardized access layer that maps SSB’s complex API endpoints into concise, agent‑friendly calls. Developers can issue natural language queries in either Norwegian or English and receive structured JSON responses that mirror the original SSB format. Internally, the server handles request translation, parameter validation, and error handling, so agents can focus on higher‑level logic rather than low‑level HTTP details. Caching is built in, reducing latency for frequently requested datasets and lowering the load on SSB’s servers.

Key capabilities include:

• Unified query interface that supports both language inputs, automatically routing them to the appropriate SSB endpoints.
• Structured data retrieval that preserves the schema of SSB’s responses, allowing downstream processing or visualization tools to consume the data directly.
• Performance optimization through a caching layer that stores recent results, improving response times for repeated queries.
• Extensibility: The MCP framework makes it easy to add new SSB datasets or custom transformations without altering the core server logic.

Typical use cases span from academic research to public policy analysis. A data scientist can ask an AI assistant for the latest unemployment rates in Oslo, and the agent will fetch the relevant SSB table, parse it, and present a concise summary or chart. A business analyst might request consumer price index trends across regions, enabling real‑time market insights without leaving the chat interface. Government agencies can embed the server into internal knowledge bases, allowing staff to retrieve statistical reports through conversational queries.

Integration with existing AI workflows is seamless: the MCP server exposes a set of tools that can be invoked by any compliant agent. Developers simply register the Ssb Mcp endpoint in their MCP configuration, and the agent’s prompt engineering can include calls like . The server returns the data in a machine‑readable format, ready for further processing or display. This tight coupling between data retrieval and AI reasoning enhances productivity and reduces the friction that typically accompanies external API consumption.