TRKR agents

Connect your own AI assistant to TRKR's synthetic market data.

TRKR simulates hundreds of complete alternative futures for real assets — every one a full ten years of daily prices, anchored to today's market and generated by a regime-aware, macro-driven engine calibrated against two decades of history. This plugin lets Claude query that data directly; ChatGPT and any other MCP client can reach the same endpoint (see below).

The simulations stay on TRKR's servers; the thinking happens in the assistant you already pay for. TRKR sends small, reduced answers — quantile bands, summary statistics, downsampled series — never the raw grid. That keeps your context small and your bill low.

Install (Claude)

/plugin marketplace add trkr-ai/trkr-agents
/plugin install trkr

Then set your API key, which you can create at trkr.ai/app/agents:

export TRKR_API_KEY=trkr_sk_...

Or, without the plugin, point any MCP client at the endpoint directly:

claude mcp add --transport http trkr https://www.trkr.ai/api/mcp \
  --header "Authorization: Bearer $TRKR_API_KEY"

ChatGPT

ChatGPT cannot send an API key to an MCP server — OpenAI's connectors support OAuth only — so it signs you in instead. There is no key to copy.

1. Turn on developer mode in ChatGPT's settings. OpenAI has moved this between Security and login, Connectors → Advanced settings and Apps → Advanced, so follow their help article rather than a path written here. It is on chatgpt.com only (not the mobile app), needs a paid plan, and on a Business or Enterprise workspace an admin must allow custom connectors first.
2. Create a connector pointing at https://www.trkr.ai/api/mcp, authentication OAuth.
3. You will land on trkr.ai to sign in and approve the connection, then return to ChatGPT with the tools available.

The skill in this repo is a Claude format, so a ChatGPT connector does not install it. The same rules travel in the server's own instructions, which ChatGPT reads at connection time — but if you use TRKR in a ChatGPT Project, pasting trkr/skills/reading-synthetic-markets/SKILL.md into the project's custom instructions is the closest equivalent.

Google Antigravity

Gemini CLI was retired in June 2026 and replaced by Antigravity (the agy command). The consumer app at gemini.google.com still has no way to add a connector, so Antigravity is the route for Google users — and it is free.

curl -fsSL https://antigravity.google/cli/install.sh | bash
agy install

Then, one command — flags must come before the name, and an http URL is detected without --type:

agy mcp add --header "Authorization: Bearer $TRKR_API_KEY" \
  trkr https://www.trkr.ai/api/mcp

Or write it to ~/.gemini/config/mcp_config.json yourself (.agents/mcp_config.json for one workspace). The field is serverUrl; Antigravity rejects the url and httpUrl spellings Gemini CLI used, and the wrong one fails as though the server were down:

{
  "mcpServers": {
    "trkr": {
      "serverUrl": "https://www.trkr.ai/api/mcp",
      "headers": { "Authorization": "Bearer trkr_sk_..." }
    }
  }
}

Drop the header entirely and Antigravity handles OAuth by itself — it registers dynamically and sends you to trkr.ai to approve, the same flow ChatGPT uses.

What you can ask

• "Why does future #42 crash in 2031?" — it reads the regimes, macro paths and prices behind that specific simulation.
• "Critique 60/30/10 SPY/AGG/GLD." — run through every future at once, with the outcome distribution rather than a single backtest.
• "Build something for a client retiring in five years." — co-build the allocation, then test it.
• "Is this data credible?" — the quality scorecard, per asset, rather than an assurance.

What's in here

The skill matters as much as the tools. Simulated ensembles invite a specific class of confident, wrong conclusion, and the skill is what stops your assistant producing them.

Not investment advice

TRKR is simulated data for analysis and stress testing. No output is a prediction about real markets. Methodology: trkr.ai/methodology.