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This repository was archived by the owner on Nov 28, 2025. It is now read-only.
Developers building AI-powered applications and autonomous systems have no clear way to integrate Pyth price feeds. Current documentation covers smart contracts and traditional APIs, but not AI agent integration.
Missing:
How to access Pyth data from AI agents (ChatGPT, Claude, custom LLMs)
Integration with AI frameworks like LangChain
Natural language price queries (e.g., "What's the current BTC price?")
Examples for autonomous trading bots and AI-driven DeFi applications
What is MCP?
Model Context Protocol (MCP) is an open standard by Anthropic that lets AI applications securely connect to external data sources. Think of it as a standardized API specifically designed for AI agents to fetch real-time data.
Why it matters for web3:
AI agents can make informed decisions based on real-time Pyth price feeds
Autonomous trading bots can access 1,930+ price feeds across 107+ chains
Developers can build AI-powered DeFi applications with reliable oracle data
Users can query prices conversationally through Claude Desktop
Solution
Add comprehensive MCP Server integration guide covering:
Setup & Installation - Get the MCP server running in minutes
Claude Desktop Integration - Query prices using natural language
Programmatic Integration - Python examples for AI agents
LangChain Integration - Build AI agents with Pyth data
Use Cases - Trading bots, portfolio management, liquidation monitoring
Best Practices - Production deployment, rate limiting, error handling