@prereason/mcp
Prereason first. Then answer.
Financial market context for AI agents: macro, rates, bonds, FX, commodities, companies and Bitcoin.
Docs · Briefings · Company briefings · Pricing · Get a key
Ask your AI where Treasury yields are. On its own, it reaches for a search result or a raw series and works out the rest by itself. When it prereasons, one get_context call brings back the context already worked out: the 30 year yield at 5.67% on 2026-10-07, the highest reading on the US Treasury's daily par yield curve since July 2001.
Why prereason?
- The analysis, and the data behind it. Each briefing arrives with the reading done: the trend over several windows, where a value sits in its own history, a company's rank among its peers and, where read, its own guidance.
- Every figure dated, every source named. Your agent can say when a number is from and where it came from.
- One call, a whole briefing. A briefing gathers the series a question needs, so the turns go to the answer rather than to lookups.
- The markets in one place. Rates and Treasuries, the Fed, FX, commodities, macro, listed companies in the USA, Japan, Korea and India, and Bitcoin.
- It describes; it never advises. Briefings say what the data shows. They never say what to buy, sell or hold.
- Quick to set up. One block of config for Claude, Cursor, Codex or VS Code, through the npm bridge or the remote server. The catalogue tools need no key; for the rest, the bridge gives you one link to approve in your browser and the key arrives in the running session; the remote server takes your API key as a header.
