dflow-mcp
MCP ServerFreeAccess real-time and historical https://kalshi.com prediction market data across events, markets, and trades. Analyze forecasts and candlestick time series to track sentiment and price action. Search and filter by tickers, mints, categories, and sports to quickly find the data you need.
Capabilities3 decomposed
real-time prediction market data access
Medium confidenceThis capability allows users to access real-time and historical prediction market data from Kalshi via a structured API that integrates seamlessly with the Model Context Protocol (MCP). It utilizes a microservices architecture to handle requests efficiently, enabling users to pull data on various events, markets, and trades without significant latency. The system is designed to filter and search through large datasets quickly, ensuring that users can retrieve relevant information based on specific criteria.
Integrates directly with Kalshi's API using a microservices architecture, allowing for seamless data retrieval and processing without the need for complex client-side logic.
More efficient than traditional REST APIs by leveraging MCP for real-time data streaming and processing.
candlestick time series analysis
Medium confidenceThis capability enables users to analyze candlestick time series data by applying statistical methods and visualizations directly within the MCP framework. It employs a combination of time series forecasting techniques and data visualization libraries to present insights on price action and market sentiment. Users can customize their analysis parameters to focus on specific time frames or market conditions, enhancing the decision-making process.
Utilizes advanced statistical methods and visualization techniques tailored for prediction market data, providing users with actionable insights directly from the MCP.
Offers more robust analytical capabilities compared to standard charting libraries by integrating real-time data feeds.
event and market filtering
Medium confidenceThis capability allows users to filter and search through prediction market data based on various criteria such as tickers, mints, categories, and sports. It leverages a powerful search algorithm that indexes the data for fast retrieval, enabling users to quickly find relevant information without sifting through irrelevant data. The filtering options are customizable, allowing users to tailor their searches to specific interests or needs.
Employs a sophisticated indexing mechanism that allows for rapid filtering and searching of prediction market data, significantly enhancing user experience compared to simpler search implementations.
Faster and more versatile than basic search tools due to its integration with the MCP and real-time data indexing.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓data analysts monitoring prediction markets
- ✓developers building financial applications
- ✓quantitative analysts studying market trends
- ✓traders looking for visual insights into market behavior
- ✓developers creating user-facing applications for market data
- ✓researchers analyzing specific market segments
Known Limitations
- ⚠Dependent on Kalshi's API availability; if the API is down, data access is limited.
- ⚠Rate limits may apply based on API usage.
- ⚠Requires familiarity with statistical analysis; may not be suitable for all user skill levels.
- ⚠Performance may degrade with very large datasets.
- ⚠Complex queries may lead to slower response times if not optimized.
- ⚠Limited to the fields provided by the Kalshi API.
Requirements
Input / Output
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Repository Details
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Access real-time and historical https://kalshi.com prediction market data across events, markets, and trades. Analyze forecasts and candlestick time series to track sentiment and price action. Search and filter by tickers, mints, categories, and sports to quickly find the data you need.
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