Squeezeos MCP Server

@timwal78

Basic information

About Squeezeos MCP Server

Institutional AI market intelligence for autonomous agents. Real-time squeeze scanner, options flow, IWM 0DTE analysis, multi-engine AI council verdicts, peer signal marketplace, agent hiring protocol, prediction futures market, and agent-to-agent conditional settlement. Pay-per-

#x402 #payment #xrpl#rlusd#usdc #ai-agents #finance #market-data#402proof

Squeezeos MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "squeezeos": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://lively-fascination-production-41fa.up.railway.app/mcp"
      ]
    }
  }
}

Squeezeos MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list by running this server in a temporary sandbox using the button above.

Overview

What is SqueezeOS?

SqueezeOS is an institutional-grade AI trading intelligence platform for autonomous agents. It offers two live MCP servers with 33 tools total, accessed via pay-per-call using RLUSD on the XRP Ledger (or USDC on Base) through the x402/HTTP‑402 protocol. Designed for AI agents, it requires no API keys, subscriptions, or accounts.

How to use SqueezeOS?

Connect any MCP client (Claude, GPT, etc.) by adding the server URL https://squeezeos-api.onrender.com/mcp with transport streamable-http. For paid endpoints, first call get_invoice to get payment details, send RLUSD on XRPL, then call verify_payment to obtain a 1‑hour access token. A Python SDK is available for automated payment flow. Free discovery endpoints and a live demo (/api/demo/council) let you test responses without paying.

Key features of SqueezeOS

33 MCP tools — 15 free, 18 paid via x402
Pay per call in RLUSD (XRPL) or USDC (Base) — no subscriptions
Token‑based access: 1‑hour HMAC‑SHA256 token after payment
Zero simulated data: returns “AWAITING_DATA” if live data unavailable
Agent Credit Bureau: portable 300–850 score from XRPL spend history
Multi‑engine oracle: 8 engines (GammaFlow, VPIN, Battle, etc.) aggregated per request

Use cases of SqueezeOS

AI agents obtain real‑time institutional trading signals with confidence scores and targets
Agents scan the $1–$50 stock universe for squeeze candidates and options picks
Peer‑to‑peer signal marketplace: list, read, and stake on signal predictions
Conditional escrow contracts settled automatically on XRPL
Regulatory event feed queries (SEC 8‑K, FDA, USPTO) with keyword search

Frequently asked questions

How do I pay for paid tools?

Call `get_invoice(endpoint_id)` → send RLUSD on XRPL mainnet to the returned address with the memo hex → call `verify_payment(invoice_id, tx_hash, agent_wallet)` → receive a 1‑hour access token to use with any paid tool.

What data sources does SqueezeOS use?

Priority order: Tradier (options chain) → Alpaca (OHLCV) → Polygon → Alpha Vantage. All data is live; if unavailable the API returns `status: "AWAITING_DATA"` — never fabricated values.

What runtime or dependencies are required?

You need Python 3, the packages in `requirements.txt`, and optionally `TRADIER_API_KEY` and `PROOF402_TOKEN_SECRET` in a `.env` file for local development. The MCP server runs via Docker/gunicorn on Render.

Is there a free way to try the service?

Yes: `curl https://squeezeos-api.onrender.com/api/demo/council` returns a full council verdict for IWM (5‑minute cache). Fifteen free tools are also available, including `demo_council`, `signal_preview`, `system_status`, and the Agent Credit Bureau score endpoint.

What is the x402 payment flow?

The x402 flow works as follows: `GET /api/{endpoint}` → server responds with HTTP 402 + payment terms → agent pays USDC/RLUSD → retry with `X-PAYMENT` header → server returns 200 with data. For SqueezeOS, the payment asset is RLUSD (issuer: `rMxCKbEDwqr76QuheSUMdEGf4B9xJ8m5De`) on XRPL mainnet.

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