Qwen has quietly become two important things at once: the dominant model family across Asian markets and one of the strongest open-weight lines anywhere for tool use and function calling. For financial applications, that combination raises a specific need — a data layer that treats Asian markets as first-class, not as an exotic add-on. That is rarer than it should be.
The Coverage Problem Qwen Users Hit
Most financial APIs are American products with American depth: full data for US tickers, thinning rapidly across Tokyo, Hong Kong, Shanghai, Seoul, and Taipei. Build a Qwen-powered research tool on such an API and it answers questions about Apple beautifully — and shrugs at TSMC's supplier network or a Nikkei mid-cap's estimate revisions.
The Eulerpool API covers 50,000+ listed companies globally — Asia included — with the same depth everywhere: full statement history, analyst estimates with revisions, ownership, insider data, segments, and supply chains, plus macro for every major economy. 100+ million data points from 250+ institutional sources, every figure with lineage.
Connecting Qwen
- MCP. The Eulerpool MCP server (250+ tools) plugs into Qwen-based agents through any MCP-speaking framework — the Qwen-Agent stack included.
- Function calling. Qwen's OpenAI-compatible tool calling consumes Eulerpool's typed schemas directly — hosted via Alibaba Cloud or self-hosted open weights.
- Self-hosted pipelines. Open weights plus a REST data API means the entire research system runs in your infrastructure — a hard requirement for many Asian financial institutions.
What the Stack Enables
- "Map TSMC's supply chain and rank the listed suppliers by revenue exposure."
- "Screen Japanese exporters for improving margins and rising estimate revisions under a weak yen."
- "Compare the China EV names on unit economics using their actual segment disclosures."
Pricing scales like inference, not like a terminal: free at 100,000 calls/month, $99/month for 1M, $499/month for 10M. Get a free key and give Qwen genuinely global data.