by jamesanz
Real-time prediction market data from Polymarket, PredictIt & Kalshi—calculated odds, contract pricing, and event filter
Fetches real-time prediction market data from Polymarket, PredictIt, and Kalshi, providing current odds, contract prices, and market search capabilities for analysis.
Prediction Markets (Polymarket, PredictIt, Kalshi) is a community-built MCP server published by jamesanz that provides AI assistants with tools and capabilities via the Model Context Protocol. Real-time prediction market data from Polymarket, PredictIt & Kalshi—calculated odds, contract pricing, and event filter It is categorized under finance, analytics data.
You can install Prediction Markets (Polymarket, PredictIt, Kalshi) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Prediction Markets (Polymarket, PredictIt, Kalshi) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
Prediction Markets (Polymarket, PredictIt, Kalshi) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Strong directory entry: Prediction Markets (Polymarket, PredictIt, Kalshi) surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Strong directory entry: Prediction Markets (Polymarket, PredictIt, Kalshi) surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Prediction Markets (Polymarket, PredictIt, Kalshi) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
I recommend Prediction Markets (Polymarket, PredictIt, Kalshi) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
According to our notes, Prediction Markets (Polymarket, PredictIt, Kalshi) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Prediction Markets (Polymarket, PredictIt, Kalshi) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
I recommend Prediction Markets (Polymarket, PredictIt, Kalshi) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
I recommend Prediction Markets (Polymarket, PredictIt, Kalshi) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Prediction Markets (Polymarket, PredictIt, Kalshi) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
showing 1-10 of 57
Real-time prediction market data in your AI workflow. Get current odds and prices from Polymarket, PredictIt, and Kalshi. No API keys required.
An MCP (Model Context Protocol) server that brings live prediction market data into AI coding environments like Cursor and Claude Desktop.
Ready to explore prediction markets? Install in seconds:
Install in Cursor (Recommended):
Or install manually:
npm install -g prediction-markets-mcp
# Or from source:
git clone https://github.com/JamesANZ/prediction-markets-mcp.git
cd prediction-markets-mcp && npm install && npm run build
get-prediction-marketsSearch for prediction markets across multiple platforms by keyword.
Parameters:
keyword (string, required): Search term (max 50 characters)
Returns:
Click the install link above or use:
cursor://anysphere.cursor-deeplink/mcp/install?name=prediction-markets-mcp&config=eyJwcmVkaWN0aW9uLW1hcmtldHMtbWNwIjp7ImNvbW1hbmQiOiJucHgiLCJhcmdzIjpbIi15IiwicHJlZGljdGlvbi1tYXJrZXRzLW1jcCJdfX0=
Requirements: Node.js 18+ and npm
# Clone and build
git clone https://github.com/JamesANZ/prediction-markets-mcp.git
cd prediction-markets-mcp
npm install
npm run build
# Run server
node build/index.js
Find prediction markets by keyword:
{
"tool": "get-prediction-markets",
"arguments": {
"keyword": "trump"
}
}
Find markets related to elections:
{
"tool": "get-prediction-markets",
"arguments": {
"keyword": "election"
}
}
| Platform | Format | Description |
|---|---|---|
| Polymarket | Percentage odds | Crypto-based prediction markets |
| PredictIt | Dollar prices | Traditional prediction markets |
| Kalshi | Regulated | US-regulated prediction markets |
https://clob.polymarket.com/marketshttps://www.predictit.org/api/marketdata/all/Built with: Node.js, TypeScript, MCP SDK
Dependencies: @modelcontextprotocol/sdk, superagent, zod
Platforms: macOS, Windows, Linux
⭐ If this project helps you, please star it on GitHub! ⭐
Contributions welcome! Please open an issue or submit a pull request.
MIT License – see LICENSE file for details.
If you find this project useful, consider supporting it:
⚡ Lightning Network
lnbc1pjhhsqepp5mjgwnvg0z53shm22hfe9us289lnaqkwv8rn2s0rtekg5vvj56xnqdqqcqzzsxqyz5vqsp5gu6vh9hyp94c7t3tkpqrp2r059t4vrw7ps78a4n0a2u52678c7yq9qyyssq7zcferywka50wcy75skjfrdrk930cuyx24rg55cwfuzxs49rc9c53mpz6zug5y2544pt8y9jflnq0ltlha26ed846jh0y7n4gm8jd3qqaautqa
₿ Bitcoin: bc1ptzvr93pn959xq4et6sqzpfnkk2args22ewv5u2th4ps7hshfaqrshe0xtp
Ξ Ethereum/EVM: 0x42ea529282DDE0AA87B42d9E83316eb23FE62c3f
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.