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Provides multi-platform prediction market data, search, tracking, and arbitrage analysis through MCP clients.
Configuration
View docs{
"mcpServers": {
"ericgrill-mcp-predictive-market": {
"command": "uv",
"args": [
"run",
"--directory",
"/path/to/mcp-predictive-market",
"python",
"-m",
"mcp_predictive_market.server"
]
}
}
}MCP Predictive Market lets you search, compare, and monitor prediction markets across multiple platforms through a single, unified interface. You can explore odds, spot arbitrage opportunities, and track markets in real time using Claude or any MCP-compatible client.
You connect your MCP client to the local or remote server and start issuing discovery and tracking commands. Use search to find markets by keyword, compare odds across platforms, and add markets to a watchlist to monitor changes over time. You can also request current odds for a specific market and look for arbitrage opportunities between platforms.
Prerequisites: You need Python installed and the UV toolchain available for running MCP servers.
Clone the project repository and install dependencies, then start the server.
git clone https://github.com/EricGrill/mcp-predictive-market.git
cd mcp-predictive-market
uv sync
# Run the server
uv run python -m mcp_predictive_market.serverConfigure the MCP server to run as a stdio (local) server that Claude can connect to. Use the following inline configuration snippet to register the server under the name prediction-market. This config uses UV as the launcher and starts the Python module that serves MCP endpoints.
{
"mcpServers": {
"prediction-market": {
"command": "uv",
"args": ["run", "--directory", "/path/to/mcp-predictive-market", "python", "-m", "mcp_predictive_market.server"]
}
}
}Here are typical usages you can try after starting the server and configuring Claude or your MCP client.
If you donβt see results from a platform, wait a moment and retry as APIs may rate-limit or platforms may be temporarily offline. If arbitrage detection isnβt returning opportunities, try broader search terms or reduce the minimum spread threshold.
For development workflows, run tests and use the provided entry points to verify integration with all supported platforms.
Search markets across all platforms by keyword.
Retrieve available market categories.
Browse markets within a specific category.
Fetch current odds for a specific market.
Compare odds for similar markets across platforms.
Add a market to your watchlist for monitoring.
List all markets currently on your watchlist with current prices.
Identify price discrepancies between platforms.