"Employee Attrition Analysis and Prediction MCP" matching MCP servers:

A simple MCP server that grabs prediction market data from polymarket, PredictIt, & Kalshi.

Provides AI agents with real-time prediction market odds from Polymarket and Kalshi, enabling them to browse active markets, retrieve detailed probabilities and trading data, and discover trending markets via x402 micropayments.

An MCP server that provides tools to query and analyze an employee knowledge graph in Neo4j, including semantic resume search, person similarity, and read-only Cypher queries.

Provides search, trending, odds, arbitrage, and category browsing for prediction markets (Polymarket & Kalshi) via the Model Context Protocol, enabling AI agents to access live market data without API keys.

Wraps a hosted prediction market API to expose estimation, sizing, scanning, ensemble, and service-information tools for experimental research, returning payment-required details on HTTP 402 responses without handling payment itself.

Enables MCP clients to search Polymarket and Kalshi, read live implied probabilities and order books, compare the same question side by side across both venues, and produce short markdown briefings with cited sources. It is read-only, needs no API keys, and performs no trading.

MCP server for querying employee data via tools like get_employees and get_employee_by_id. Serves as a proof-of-concept for integrating Pega applications with AI agents.

Unified access to prediction market data from Kalshi and Polymarket, enabling natural language queries for real-time odds, orderbooks, and trade history.

The Behavioural Prediction MCP Server provides AI-powered tools to analyze wallet behaviour prediction,fraud detection and rug pull prediction.

AI-powered terrain analysis for any location on Earth. Uses super-resolution and computes environmental risk metrics including erosion, water flow, and a composite Site Intelligence Score.

Self-hostable, read-only Taiwan stock-analysis MCP server that retrieves market data and computes reproducible indicators.

Enables querying options chains and estimating gamma exposure for ETFs and liquid underlyings, including proxy gamma calculations and historical gamma snapshots.

Enables distribution-free split conformal prediction through MCP, producing adaptive prediction sets with finite-sample marginal coverage guarantees for agent routing, classification, and structured decision tasks.

A powerful Model Context Protocol (MCP) server for seamless Jira integration with AI assistants like Claude. Features advanced search capabilities, intelligent pod aliases, comprehensive ticket analysis, and full API support.

This MCP server provides current weather, 1-16 day forecasts, travel recommendations, and city comparisons using Open-Meteo. It requires no API key and includes a transparent agent-friendly interface.

Enables MCP clients to query live Polymarket and Kalshi odds, price history, movers, resolved and closing markets, cross-platform gaps, watch-based change tracking, and X/Twitter sentiment in a single call, paying per request in USDC on Base via x402. Also surfaces ticker-linked event markets and a free example call so agents can inspect results before spending.

Real-time prediction market intelligence for AI agents. Query Polymarket and Kalshi markets, wallet profiles, smart money leaderboards, social pulse signals, price candlesticks, and orderbook data — 13 agents, one MCP connection. Powered by 1.1TB+ of historical data.

Enables static analysis of code snippets and public GitHub repositories using ruff and semgrep through a secure MCP SSE server.

Provides current weather, forecasts, and travel recommendations via Open-Meteo, enabling natural language queries about weather conditions.

MCP server that provides real-time weather data, forecasts, city weather comparisons, and travel recommendations using the OpenMeteo API, enabling AI agents to answer weather-related queries and suggest optimal travel conditions.