[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_114":115},"routes/modules.$creator.$moduleId",{"_14":15,"_16":17,"_18":19,"_20":21},"routes/modules.$creator.$moduleId.endpoints",{"_11":12,"_13":-5},"error","Module '@isakskogstad/scb-mcp' is not configured","tools","module",{"_20":22,"_23":24,"_25":26,"_27":28,"_29":30,"_31":32,"_33":26,"_34":-5,"_35":36,"_37":-5,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":48,"_56":57,"_58":59,"_60":-5,"_61":-5,"_62":-5,"_63":-5,"_64":65,"_66":67,"_68":69,"_70":71,"_72":73,"_74":-5,"_75":-5,"_76":-5,"_77":48,"_78":-5,"_79":80,"_81":82,"_83":84,"_85":86,"_87":88,"_89":90,"_91":92},"apiUrl","https://odel.app/api","creator","isakskogstad","moduleId","scb-mcp","@isakskogstad/scb-mcp","displayName","SCB MCP","tagline","MCP server for Statistics Sweden (SCB) - 1200+ tables with population, economy, environment data","iconKey","https://avatars.githubusercontent.com/u/149165200?v=4","category","data","status","published","metaDescription","metaKeywords","deploymentType","external","workerName","bindingName","mcpConfig","{\"url\":\"https://scb-mcp.onrender.com/mcp\",\"transport\":\"streamable-http\",\"authType\":\"none\"}","pricingModel","free","creatorUserId","system:external-import","createdAt",1781363450000,"updatedAt",1781499666000,"sourceRegistry","official-mcp-registry","sourceUrl","https://registry.modelcontextprotocol.io/v0/servers?search=io.github.isakskogstad%2Fscb-mcp","sourceVerified",true,"importedAt","upstreamStars",8,"upstreamUpdatedAt",1776851311000,"detectedTransport","detectedAuthType","probeStatus","lastProbedAt","githubRepoUrl","https://github.com/isakskogstad/SCB-MCP","githubRepoFullName","isakskogstad/SCB-MCP","releaseId","ext-isakskogstad-scb-mcp","version","2.5.3","descriptionMarkdown"," $\"MCP$ \n\n[![MCP Registry](https://img.shields.io/badge/MCP%20Registry-Published-brightgreen)](https://registry.modelcontextprotocol.io/servers/io.github.isakskogstad/scb-mcp)\n[![MCP Protocol](https://img.shields.io/badge/MCP-2025--03--26-green)](https://modelcontextprotocol.io/)\n\n# 📊 SCB MCP Server\n\nSCB MCP är server som LLM:s och AI-chatbotar kan använda för att söka, hitta och hämta officiell data och statistik från Statistikbyrån (SCB). Det omfattar 1 200+ statistiktabeller med data om befolkning & demografi, ekonomi & finans, miljö, arbetsmarknad, utbildning och transport. Perfekt för att bygga interaktiva instrumentpaneler, forskningsverktyg och utbildningsapplikationer.\n\n---\n\n## Översikt\n\n

🇬🇧 Overview

\n\nThe SCB MCP server provides seamless integration with **Statistics Sweden's PxWebAPI 2.0**, enabling LLM:s to access:\n\n- **Population & Demographics**: Regional data, migrations, births, deaths (312+ regions)\n- **Economy & Finance**: GDP, taxes, business statistics, national accounts\n- **Environment**: Greenhouse gas emissions, water/waste management, sustainability metrics\n- **Labor Market**: Employment, unemployment, occupational data, skills matching\n- **Education**: Student statistics, course enrollments, skills development\n\nData ranges from 1950s to present (monthly/quarterly updates). Real-time population statistics updated to November 2025.\n\n

\nSCB MCP-servern ger sömlös integrering med Statistikbyråns (SCB) PxWebAPI 2.0, vilket gör det möjligt för LLM:s att tillgå:\n\n- **Befolkning & demografi**: Regionaldata, migrationer, födslar, dödsfall (312+ regioner)\n- **Ekonomi & finans**: BNP, skatter, företagsstatistik, nationalräkenskaper\n- **Miljö**: Växthusgaser, vatten/avfallshantering, hållbarhetsvärdena\n- **Arbetsmarknad**: Sysselsättning, arbetslöshet, yrkesdata, kompetensmatchning\n- **Utbildning**: Studentstatistik, kursanmälningar, kompetensutveckling\n\n---\n\n

🇬🇧 Key features (English)

\n\n| Feature | Description |\n| ------------------------ | ---------------------------------------------------------------------------------------------- |\n| **Comprehensive Access** | 1,200+ tables, 312+ regions, 75+ years of historical data |\n| **Smart Querying** | Natural language search, region code resolution (\"Lerum\" → 1441), TOP() & wildcard support |\n| **Fuzzy Matching** | \"Goteborg\" matches \"Göteborg\", \"Malmo\" matches \"Malmö\" |\n| **Developer-Friendly** | Full documentation, clear errors with suggestions, selection validation, metadata in responses |\n| **Production-Ready** | Rate limiting (30 req/10s), consistent behavior, proper data types, language support (SV/EN) |\n| **Swedish by Default** | All tools use Swedish (sv) as default for best search results |\n| **Real-Time Data** | Monthly/quarterly updates, population data to November 2025 |\n\n

\n\n## Huvudfunktioner\n\n| Funktion | Beskrivning |\n| ------------------------ | -------------------------------------------------------------------------------------------- |\n| **Omfattande åtkomst** | 1 200+ tabeller, 312+ regioner, 75+ års historiska data |\n| **Smart sökning** | Naturspråkig sökning, regionkodupplösning (\"Lerum\" → 1441), TOP() & wildcard-stöd |\n| **Fuzzy matching** | \"Goteborg\" matchar \"Göteborg\", \"Malmo\" matchar \"Malmö\" |\n| **Utvecklarvänlig** | Fullständig dokumentation, tydliga felmeddelanden, valideringsmöjligheter, metadata i svaren |\n| **Produktionsklar** | Rate limiting (30 req/10s), konsekvent beteende, rätt datatyper, språkstöd (SV/EN) |\n| **Svenska som standard** | Alla verktyg använder svenska (sv) som default för bästa sökresultat |\n| **Aktuell data** | Månatliga/kvartalsvisa uppdateringar, befolkningsdata till november 2025 |\n\n---\n\n## 🚀 Installation\n\nServern körs lokalt via stdio. Klona, bygg och peka din MCP-klient mot `dist/index.js`.\n\n```bash\ngit clone https://github.com/isakskogstad/SCB-MCP.git\ncd SCB-MCP\nnpm install\nnpm run build\n```\n\n### Claude Code (CLI)\n\n```bash\nclaude mcp add scb -- node /absolut/sökväg/till/SCB-MCP/dist/index.js\n```\n\n### Claude Desktop / Codex / Gemini / Cursor (stdio)\n\nLägg till i klientens MCP-konfiguration (t.ex. `~/Library/Application Support/Claude/claude_desktop_config.json` för Claude Desktop):\n\n```json\n{\n \"mcpServers\": {\n \"scb\": {\n \"command\": \"node\",\n \"args\": [\"/absolut/sökväg/till/SCB-MCP/dist/index.js\"]\n }\n }\n}\n```\n\n

🇬🇧 Installation (English)

\n\nThe server runs locally over stdio. Clone, build, and point your MCP client to `dist/index.js`.\n\n```bash\ngit clone https://github.com/isakskogstad/SCB-MCP.git\ncd SCB-MCP\nnpm install\nnpm run build\n```\n\n#### Claude Code (CLI)\n\n```bash\nclaude mcp add scb -- node /absolute/path/to/SCB-MCP/dist/index.js\n```\n\n#### Claude Desktop / Codex / Gemini / Cursor (stdio)\n\n```json\n{\n \"mcpServers\": {\n \"scb\": {\n \"command\": \"node\",\n \"args\": [\"/absolute/path/to/SCB-MCP/dist/index.js\"]\n }\n }\n}\n```\n\n

\n\n---\n\n## Användarguide\n\n### 1. Sök efter statistiktabeller\n\n```python\n# Hitta befolkningsrelaterade tabeller\nresults = scb.search_tables(query=\"befolkning statistik\", limit=10)\n\n# Filtrera efter kategori\nresults = scb.search_tables(query=\"miljö\", category=\"environment\", limit=5)\n```\n\n

🇬🇧 Usage guide (English)

\n\n### 1. Search for statistical tables\n\n```python\nresults = scb.search_tables(query=\"population\", limit=10)\nresults = scb.search_tables(query=\"environment\", category=\"environment\", limit=5)\n```\n\n

\n\n---\n\n### 2. Hitta regionkoder\n\n```python\n# Lerum kommun\nregion = scb.find_region_code(query=\"Lerum\")\n# Returnerar: code=\"1441\", name=\"Lerum\"\n\n# Större regioner\nregion = scb.find_region_code(query=\"Stockholm\")\n# Returnerar: code=\"01\" (län), code=\"0180\" (kommun)\n\n# Fuzzy matching - fungerar utan svenska tecken\nregion = scb.find_region_code(query=\"Goteborg\")\n# Returnerar: code=\"1480\", name=\"Göteborg\"\n```\n\n

🇬🇧 Resolve region codes (English)

\n\n```python\nregion = scb.find_region_code(query=\"Lerum\")\nregion = scb.find_region_code(query=\"Stockholm\")\n\n# Fuzzy matching - works without Swedish characters\nregion = scb.find_region_code(query=\"Goteborg\")\n# Returns: code=\"1480\", name=\"Göteborg\"\n```\n\n

\n\n---\n\n### 3. Hämta data\n\n```python\n# Medelålder i Lerum 2024\ndata = scb.get_table_data(\n tableId=\"TAB637\",\n selection={\n \"Region\": [\"1441\"],\n \"Kon\": [\"1+2\"],\n \"Tid\": [\"2024\"],\n \"ContentsCode\": [\"BE0101G9\"]\n }\n)\n# Resultat: Medelålder i Lerum 2024: 40.1 år\n```\n\n

🇬🇧 Fetch data (English)

\n\n```python\ndata = scb.get_table_data(\n tableId=\"TAB637\",\n selection={\n \"Region\": [\"1441\"],\n \"Kon\": [\"1+2\"],\n \"Tid\": [\"2024\"],\n \"ContentsCode\": [\"BE0101G9\"]\n }\n)\n```\n\n

\n\n---\n\n## Best practices\n\n| Problem | Lösning |\n| ---------------------- | --------------------------------------------------------------------- |\n| **Stor datamängd?** | Använd alltid `preview_data()` först för att testa |\n| **För mycket data?** | Använd `\"TOP(5)\"` istället för `\"*\"` för tidsperioder |\n| **Felaktiga koder?** | Anropa `get_table_variables()` först — koder varierar mellan tabeller |\n| **Osäker på enheter?** | Kontrollera variabeletikett för enheter (kt, ton, procent osv.) |\n\n

🇬🇧 Best practices (English)

\n\n| Issue | Solution |\n| ----------------------- | -------------------------------------------------------------- |\n| **Large dataset?** | Always use `preview_data()` first to test |\n| **Too much data?** | Use `\"TOP(5)\"` instead of `\"*\"` for time periods |\n| **Wrong codes?** | Call `get_table_variables()` first — codes vary between tables |\n| **Unsure about units?** | Check variable label for units (kt, tonnes, percent, etc.) |\n\n

\n\n---\n\n## Praktiska exempel\n\n### Ex: Befolkningstrend Lerum vs Stockholm\n\n```python\n# Jämför två regioner över tid\ndata = scb.get_table_data(\n tableId=\"TAB637\",\n selection={\n \"Region\": [\"1441\", \"0180\"], # Lerum och Stockholm\n \"Kon\": [\"1+2\"],\n \"Tid\": [\"TOP(5)\"],\n \"ContentsCode\": [\"BE0101G9\"]\n }\n)\n# Stockholm: 41.0 år (2024), Lerum: 40.1 år (2024)\n# Trend: Stockholm åldras snabbare\n```\n\n

🇬🇧 Example 1: Population trends (English)

\n\n```python\ndata = scb.get_table_data(\n tableId=\"TAB637\",\n selection={\n \"Region\": [\"1441\", \"0180\"], # Lerum and Stockholm\n \"Kon\": [\"1+2\"],\n \"Tid\": [\"TOP(5)\"],\n \"ContentsCode\": [\"BE0101G9\"]\n }\n)\n# Stockholm: 41.0 years (2024), Lerum: 40.1 years (2024)\n```\n\n

\n\n---\n\n## Resurser\n\n- **SCB-databas**: https://www.scb.se/\n- **API-dokumentation**: https://www.scb.se/en/services/open-data-api/pxwebapi/\n- **Dataexplorer**: https://pxweb.scb.se/pxweb/en/\n\n---\n\n**Av: Isak Skogstad**\n","changelogMarkdown","videoKey","requiredSecretsJson","publishedAt","priceCents","trialDays",0,"categoryDisplayName","Data & Analytics","upstream",{"_95":96,"_97":-5,"_98":99,"_100":101,"_102":103},"requiredSecrets",[],"tags",[],"assets",[],"stats",{"_93":80,"_94":80},"ratingAvg","reviewCount","topics",[104,105,106,107,108,109,110,111,112,113],"license","language","TypeScript","registryName","io.github.isakskogstad/scb-mcp","homepage","https://scb-mcp.onrender.com/","mcp","mcp-server","mcp-servers","official-statistics","open-data","remote-mcp-server","scb","statistics","sweden","sweden-data","ENV",{"_116":117,"_118":119,"_120":121},"ENVIRONMENT","production","TURNSTILE_SITE_KEY","0x4AAAAAAB8-rEI2gNDf_QhU","SENTRY_DSN","https://45fd1229f78089d5c3ee78be128030e1@o4510583261757440.ingest.de.sentry.io/4510584253448272"]