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Prediction Market Friction Tracker

Prediction Market Friction Tracker

Remote
github.com/ndrysdal-byteFinance0Updated 10w ago
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About Prediction Market Friction Tracker

Prediction Market Friction Tracker provides structured KYC, fee, withdrawal, and API-access information for prediction-market venues. It is intended for AI agents checking trading constraints, with venue recommendations and a paid feed of detected changes.

Key features

  1. 01Browse venue friction data and confidence
  2. 02Retrieve a venue's fee and KYC details
  3. 03Recommend venues from natural-language criteria
  4. 04Track detected changes through a paid feed

Use cases

  1. 01Check KYC requirements before routing a trade
  2. 02Compare venue fees and withdrawal terms
  3. 03Find venues matching API-access criteria
  4. 04Monitor changes to venue policies

MCP support

Provides a streamable-HTTP MCP server at `/mcp/` with tools to list venues, retrieve venue details, recommend a venue, and describe the change feed. The change feed itself is accessed through an x402-gated HTTP endpoint.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://prediction-friction-tracker-production.up.railway.app/mcp/
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

Prediction market friction tracker

Structured KYC, fee, and withdrawal data across 12 prediction-market venues, plus a change feed for when those terms move and a natural-language "which venue is best for X" recommendation tool. Built for AI agents that need to check execution friction before routing a trade — not for humans clicking around a dashboard.

Live now: https://prediction-friction-tracker-production.up.railway.app

For agents: three ways in

  1. Plain HTTP — GET /friction/venues, GET /friction/venue/{slug}, GET /friction/changes?since=<ISO8601>. Full OpenAPI spec at /openapi.json, interactive docs at /docs, agent-readable summary at /llms.txt.
  2. MCP — a streamable-HTTP MCP server mounted at /mcp/, exposing list_venues, get_venue, recommend_venue, and get_changes_info as tools. Point any MCP-compatible client at the /mcp/ URL directly.
  3. x402 — /friction/changes (the time-sensitive change feed) is gated by the x402 protocol: unpaid requests get a real 402 with a payment challenge; pay $0.05 USDC on Base mainnet and retry to get the data. This is live, verified end-to-end with real money, not a demo — see api.py for the CDP-facilitator wiring.

Endpoints

EndpointCostWhat it returns
GET /friction/venuesFreeCurrent snapshot of every tracked venue. Optional ?confidence=verified|stale|unconfirmed filter.
GET /friction/venue/{slug}FreeOne venue's current fee/KYC/withdrawal/API-access data, e.g. /friction/venue/kalshi.
GET /friction/changes?since=<ISO8601>$0.05 USDC (x402)Append-only log of every detected change since a timestamp — the time-sensitive product.

Every record carries a confidence field: verified (spot-checked or high-confidence extraction), stale (source was unreachable, showing a cached value), or unconfirmed (LLM extraction was ambiguous). Treat unconfirmed as a lead to verify against the venue directly, not a fact to trade on.

MCP tools

  • list_venues(confidence) — browse/filter the current snapshot.
  • get_venue(slug) — one venue's full data.
  • recommend_venue(query) — free-text "which venue is best for lowest fees on high-frequency trading" / "I don't want to do KYC" / "API access without a wallet" style questions, reasoned over the current dataset. Says so explicitly rather than guessing when a query depends on data this tracker doesn't have (liquidity, volume, spread, uptime).
  • get_changes_info() — describes the paid change feed (URL, price) without reimplementing it for free.

What's here

FileWhat it does
schema.pyThe data model — one VenueFriction record per venue, plus the VenueRecommendation response shape
venues.pyThe 12 tracked venues and their policy-page source URLs
scrapers/base.pyFetches and cleans raw policy-page text (requests + Playwright fallback for JS-rendered pages)
extract.pySends raw page text to Claude, gets back a structured VenueFriction matching the schema
recommend.pyNatural-language venue recommendation — reasons over the current dataset via Claude, structured-output constrained to real venue slugs
reference_check.pyCross-checks scraped fees against a third-party source (TradeBlock), flags divergences for human review
storage.pySQLite: current_state table (latest snapshot) + change_log table (append-only, the paid product)
diff.pyCompares a fresh extraction to the stored one, writes a ChangeEvent for anything that moved
run_pipeline.pyOrchestrates fetch → extract → diff → store, for all 12 venues
api.pyFastAPI server — the HTTP endpoints above, x402 payment gating, MCP mount
mcp_server.pyThe MCP tool definitions, mounted into api.py at /mcp/
test_pipeline_logic.py, test_recommend_logic.pyPure-logic tests, no API key needed

Running it locally

pip install -r requirements.txt
python test_pipeline_logic.py      # no API key needed, proves storage/diff logic
python test_recommend_logic.py     # no API key needed, proves recommendation logic
export ANTHROPIC_API_KEY=sk-ant-...
python run_pipeline.py             # real scrape -> extract -> store, all 12 venues
uvicorn api:app --reload           # boots the API on localhost:8000

Then in another terminal:

curl http://localhost:8000/friction/venues
curl http://localhost:8000/friction/venue/kalshi
curl "http://localhost:8000/friction/changes?since=2020-01-01T00:00:00Z"

See CLAUDE.md for environment quirks, Claude API usage notes, and the data-quality/confidence model in more depth.

Informational only — not financial or legal advice. Verify directly with the venue before acting on any figure returned here.

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