Nordic Economics MCP

Nordic Economics MCP

Semantic search over Nordic economic data — market announcements, quarterly reports (162 companies), macro data (NO/SE/DK/FI), commodity prices, and press releases. 180,000+ vectors.

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README

Nordic Financial MCP

<!-- mcp-name: io.github.AIDataNordic/nordic-financial-mcp -->

A production-grade semantic search server for Nordic financial markets — built for autonomous AI agents. 173,000+ vectors across exchange filings, company reports, macro data, and commodity prices.

Live endpoint: https://mcp.aidatanorge.no/mcp Transport: streamable-http Registry: MCP Registry · Glama.ai · mcp.so


Connect

Add to your MCP client config:

{
  "mcpServers": {
    "nordic-financial": {
      "type": "streamable-http",
      "url": "https://mcp.aidatanorge.no/mcp"
    }
  }
}

Or with Claude Code:

claude mcp add --transport http nordic-financial https://mcp.aidatanorge.no/mcp

What This Is

AIDataNorge is a full-stack data pipeline and semantic search system that ingests, processes, and indexes financial data from Nordic markets into a vector database optimized for AI agent queries. It exposes data through a Model Context Protocol (MCP) server, making it natively compatible with Claude, LangChain, and other LLM-based agents.

The system is designed with autonomous machine-to-machine consumption in mind, including support for emerging agent payment protocols. The database is updated nightly.


MCP Tools

search_filings(
    query="Nordea net interest margin outlook 2025",
    report_type="quarterly_report",  # or annual_report, macro_summary, press_release
    country="SE",                    # NO, SE, DK, FI
    limit=10
)
# Returns semantically ranked chunks with reranking, company metadata, and source URL

get_company_info(org_number)
# Norwegian company lookup via Brønnøysundregistrene

get_market_data(ticker)
# Live price and key ratios via Yahoo Finance

Search quality: Two-stage retrieval — dense vector search (all-mpnet-base-v2) followed by cross-encoder reranking (ms-marco-MiniLM-L-6-v2) for high-precision results.


Data Coverage

Source Geography Content Volume
NewsWeb Norway Exchange filings 2020– ~30,000+ docs
MFN Nordics SE / DK / FI Annual & quarterly reports, 162 companies ~90,000+ docs
GlobeNewswire NO/SE/DK/FI Press releases, updated hourly ~8,600 docs
SEC EDGAR Nordic ADRs 20-F / 6-K filings Ongoing
IR websites SE/DK/FI Annual/quarterly PDFs ~3,000 docs
Macro NO Norway GDP, CPI, rates, housing 24 quarters
Macro Nordics SE/DK/FI Rates, housing, credit, power 72 quarters
Commodity Global/Nordic Brent, salmon, and more Per quarter

Total: 173,000+ vectors · Updated nightly


Architecture

Data Sources                 Pipeline                  Serving
─────────────────            ─────────────────         ─────────────────
Oslo Børs (NewsWeb)    →                               
SEC EDGAR (20-F/6-K)   →     Python ingest scripts  →  Qdrant
MFN Nordics (SE/DK/FI) →     + Playwright scraping  →  Vector Database
GlobeNewswire          →     + PDF extraction        →  (173,000+ vectors)
SSB / Norges Bank      →     + Chunking              →        ↓
SCB / DST / stat.fi    →     + Embeddings            →  MCP Server
ENTSO-E (power prices) →      (all-mpnet-base-v2)   →  (FastMCP 3.2)
IR websites (PDF)      →                                      ↓
                                                       AI Agents / LLMs

Technical Stack

Data ingestion

  • Python with Playwright for JavaScript-rendered IR pages and MFN feed
  • PyMuPDF (fitz) for PDF text extraction
  • Paragraph-aware chunking (512-token chunks, 100-token overlap)
  • Batch embedding with sentence-transformers/all-mpnet-base-v2

Storage & search

  • Qdrant vector database (self-hosted)
  • Cosine similarity search
  • Cross-encoder reranking (ms-marco-MiniLM-L-6-v2)

Serving

  • FastMCP 3.2 over HTTP (/mcp endpoint)
  • Cloudflare Tunnel — rate limited to 60 req/min per IP
  • Compatible with Claude, LangChain, and any MCP-capable agent

Infrastructure

  • Ubuntu Server 24 LTS, self-hosted
  • 14 GB RAM, ~950 GB storage (LVM)
  • Automated cron jobs for continuous ingestion
  • Bitcoin full node (LND) for Lightning Network payments
  • DigiByte full node with DigiRail and DigiDollar Oracle node

Agent Payment Infrastructure

The system is built with autonomous agent monetization in mind:

Lightning Network (L402) Running a full Bitcoin node with LND enables L402 — the HTTP payment protocol for autonomous agents. Agents can discover the API, receive a Lightning invoice, pay in millisatoshis, and get access — all without human intervention.

DigiRail / DigiDollar Also running a DigiByte full node with DigiRail (an agent payment protocol similar to L402) and a DigiDollar Oracle node. DigiDollar is the world's first UTXO-native decentralized stablecoin, implemented directly in DigiByte Core v9.26. The oracle node contributes to the decentralized price feed that maintains DigiDollar's USD peg — 15 of 30 randomly selected oracle nodes must reach consensus every ~25 minutes using Schnorr signatures.

This dual payment infrastructure (Bitcoin/Lightning + DigiByte/DigiRail) positions AIDataNorge to serve agents operating across different payment ecosystems.


Ingest Pipeline Design

Each data source has a dedicated ingest script with:

  • Idempotent processing via MD5-based point IDs (upsert-safe)
  • processed.txt log to avoid redundant re-fetching
  • nohup + cron scheduling for unattended overnight runs
  • Structured payload per chunk: source, country, ticker, company_name, report_type, published_date, chunk_index, total_chunks

Chunking strategy: paragraphs are accumulated until reaching the 512-token model window. Chunks never split mid-sentence. 100-token overlap ensures context continuity across chunk boundaries.


Cron Schedule

Time Job
07:00 daily NewsWeb update (Oslo Børs)
08:00–18:00 hourly (Mon–Fri) GlobeNewswire (NO/SE/DK/FI)
Quarterly Macro Norway (SSB + Norges Bank)
Quarterly (pending) Macro Nordics (SCB/DST/stat.fi + ENTSO-E)

Skills Demonstrated

  • RAG system design — end-to-end pipeline from raw data to semantic search
  • Web scraping at scale — Playwright, RSS feeds, REST APIs, PDF extraction
  • Vector database operations — Qdrant, embedding models, reranking
  • MCP server development — FastMCP, tool design for LLM agents
  • Linux server administration — LVM, process management, cron, nohup
  • Blockchain infrastructure — Bitcoin full node + LND, DigiByte full node + oracle
  • Python engineering — async pipelines, error handling, idempotent design
  • Financial data domain knowledge — Nordic exchanges, regulatory filings, macro data

Status (April 2026)

  • NewsWeb backfill complete: 500,000 → 669,999
  • MFN Nordics: 162 Large/Mid Cap companies (SE/DK/FI)
  • Macro Norway complete: 2020Q1–2025Q4
  • Macro Nordics complete: SE/DK/FI 2020Q1–2025Q4
  • MCP server: live at https://mcp.aidatanorge.no/mcp
  • Published: MCP Registry · Glama.ai · mcp.so
  • GitHub topics: mcp mcp-server nordic finance semantic-search qdrant norway sweden denmark finland
  • L402 / DigiRail: infrastructure in place, monetization layer in development

Built and operated by a single developer as a passion project exploring the intersection of Nordic financial data, AI agents, and decentralized payment infrastructure.

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