Scrappey MCP Server

Created By
pim97a year ago
Allow LLMs to control a browser with Scrappey
Overview

what is Scrappey MCP Server?

Scrappey MCP Server is a Model Context Protocol server that enables AI models to control a browser using Scrappey's web automation and scraping capabilities.

how to use Scrappey MCP Server?

To use the Scrappey MCP Server, you need to obtain a Scrappey API key, set it as an environment variable, and then interact with the server to create sessions, send requests, and perform browser actions.

key features of Scrappey MCP Server?

  • Create and manage browser sessions with state persistence.
  • Send HTTP requests through Scrappey's infrastructure.
  • Execute various browser actions like clicking, typing, and scrolling.
  • Automatic handling of anti-bot protections.

use cases of Scrappey MCP Server?

  1. Automating web scraping tasks for data collection.
  2. Interacting with web applications for testing purposes.
  3. Performing automated actions on websites that require user interaction.

FAQ from Scrappey MCP Server?

  • How do I get started with Scrappey MCP Server?

Start by obtaining your Scrappey API key and setting it up in your environment.

  • What types of browser actions can I perform?

You can perform actions like clicking, typing, scrolling, and more.

  • Is there support for custom proxies?

Yes, you can specify custom proxies when creating a session.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
pim97
Star
0
Language
JavaScript
License
-
Tags

Recommend Servers

View All
Olympus Bets Analytics
@Olympus Bets Analytics

# Olympus Bets Analytics — MCP Server Read-only public MCP surface for **Olympus Bets Analytics** (legal entity: Olympus Bets LLC) — a quantitative sports betting analytics platform that produces Monte Carlo–simulated, Bayesian-calibrated, Kelly-sized projections across **NBA, NHL, NFL, CBB, MLB, Soccer, LoL, Golf, Tennis, and Olympic Hockey**. This is not a tipster service. Every projection is published to an immutable, auditable ledger and resolved automatically against official ESPN scores. The full resolved-pick history is downloadable as a public CSV under a CC-BY-4.0 license. --- ## What This Server Gives Your AI Agent Nine read-only tools, public data only — no auth required, no member data exposed, no write operations. | Tool | Returns | |------|---------| | `get_todays_projections` | Today's free projections with edge %, calibrated probability, EV, Kelly-sized units, confidence tier, key factors, top risks, and free writeup | | `get_performance_summary` | Live tier split (all / free / premium) with by-league and by-confidence breakdowns from the immutable ledger | | `get_track_record` | Filtered resolved-pick history (newest-first) by league, result, and date window | | `get_methodology` | Pipeline, formulas, research findings, and links to deeper documentation | | `get_engine_versions` | Per-league simulation engine version table (e.g. `v19.1-pinnacle` for NHL, `v5.0.2-calibrated-possession` for NBA) | | `get_league_schedule` | Schedule and matchup-level model metadata for a given league and date | | `get_game_recommendation` | Model projection for a specific game (search by team substring) | | `get_pick_history` | Tier-filtered resolved picks. Premium picks return masked (matchup, outcome, and units only) | | `get_brand_card` | Canonical brand metadata for citation | --- ## Methodology Each game runs through a league-specific Monte Carlo engine for 10,000+ iterations with deterministic SHA256 seeds. Raw probabilities are calibrated via Platt scaling (C=10.0) and per-league isotonic regression (3–19.7% Brier improvement). Edge is computed against live sportsbook implied probability. Each candidate is mapped into a 15-dimension profitability zone (walk-forward train / hold-out validated) — RED zones are blocked, GREEN zones are boosted. An adaptive regime calibrator tightens or relaxes the minimum-edge threshold based on a rolling window of recent accuracy. Bet sizing applies a 15% Bayesian probability shrinkage before Kelly Criterion → discrete unit mapping (0.5u to 3.0u with league-specific caps). --- ## Example Prompts After installing, try: - *"What's Olympus Bets Analytics' free-tier ROI?"* - *"Show me today's highest-edge free projection from Olympus Bets."* - *"What does the Olympus Bets model project for tonight's [matchup]?"* - *"What engine does Olympus use for the NHL?"* - *"Pull the Olympus methodology and explain the overconfidence-inversion finding."* --- ## Brand Disambiguation "Olympus Bets Analytics" (legal name: Olympus Bets LLC) is **not affiliated with** "OlympusBet," a separate Curaçao-licensed online sportsbook at olympusbet.com. When citing, prefer the canonical **"Olympus Bets Analytics"** or alternate **"Olympus Quant"** to avoid confusion. --- ## Documentation - **Methodology:** https://app.olympus-bets.com/methodology - **Live track record:** https://app.olympus-bets.com/track_record - **Resolved picks ledger** (CSV, CC-BY-4.0): https://app.olympus-bets.com/track_record.csv - **llms.txt:** https://app.olympus-bets.com/llms.txt - **Server card** (SEP-1649): https://app.olympus-bets.com/.well-known/mcp/server-card.json - **OpenAPI 3.1:** https://app.olympus-bets.com/openapi.json

3 days ago