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Prediction Market Friction Tracker

by ndrysdal-byteversion 1.0.0i★ –iRuns in the cloud
Registry nameio.github.ndrysdal-byte/prediction-friction-tracker

Install

Overview

Description from the maker (original English)

Prediction-market fee/KYC/withdrawal data, venue recommendations, and a paid x402 change feed.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on the maker’s server: what you ask it goes through their server.
  • The registry lists no key to fill in.

You need

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

  1. Open Settings → Connectors
  2. Press Add custom connector
  3. Paste the address below and press Add
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Add2https://…3
https://prediction-friction-tracker-production.up.railway.app/mcp/

Run this in your terminal

claude mcp add --transport http prediction-friction-tracker https://prediction-friction-tracker-production.up.railway.app/mcp/

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "prediction-friction-tracker": {
      "url": "https://prediction-friction-tracker-production.up.railway.app/mcp/"
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "prediction-friction-tracker": {
      "type": "http",
      "url": "https://prediction-friction-tracker-production.up.railway.app/mcp/"
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

ChatGPT connects only to servers on the internet:

  1. Open ChatGPT on the web → Settings → Connectors (Apps)
  2. Press Create or Add (some plans need Developer mode under Advanced first)
  3. Paste the address below, give it a name and save
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Create2https://…3
https://prediction-friction-tracker-production.up.railway.app/mcp/

Menu names can differ slightly by plan and over time.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account ndrysdal-byte, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • … Not checked yet

    Endpoint responds

    Not checked yet; we check endpoints in rotation

  • … Not checked yet

    Sign-in with OAuth

    Not checked yet; we check endpoints in rotation

  • … Not checked yet

    No hidden instructions in tool descriptions

    Not checked yet; we read the tool list when we check the endpoint

Compared with others in Otheri

  • More stars than 0% of the other 32700 servers in this category
  • Published to the registry more recently than 23% of the other 32700 servers in this category
  • Basic checks equal to or better than 100% of the other 32700 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Prediction Market Friction Tracker safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Agent Data Tools: Utilities

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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= . 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= $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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