Pyth Network launched its Pro MCP Server 1.1, enabling AI agents to access tick-level price history across multiple asset classes. The update allows users to verify which data feeds a plan covers and request any asset pair by name, spanning markets including crypto, foreign exchange, equities, metals, rates, and net asset values. The launch addresses growing demand for real-time market data analytics as traders increasingly rely on advanced data capabilities to inform trading decisions.
Pro MCP Server 1.1 Delivers Tick-Level Price History Access
The Pro MCP Server 1.1 provides AI agents with tick-level price history, a granular data format capturing individual price movements. Users can check which feeds a specific plan covers and request any asset pair by name across various markets. Pyth Network announced the launch via its X account, highlighting the server's capability to deliver comprehensive market data.
Multi-Asset Coverage Spans Crypto to Traditional Markets
The server covers crypto, foreign exchange, equities, metals, rates, and net asset values. This multi-asset approach positions Pyth Network as a provider of high-fidelity market data across both digital and traditional financial instruments. The integration of AI technology aims to enhance decision-making processes for traders and investors by providing real-time analytics capabilities.
FAQ
What does Pyth Network's Pro MCP Server 1.1 enable?
The Pro MCP Server 1.1 enables AI agents to access tick-level price history and allows users to request any asset pair by name across multiple markets including crypto, foreign exchange, equities, metals, rates, and net asset values.
Which markets does the Pro MCP Server 1.1 cover?
The server covers crypto, foreign exchange (FX), equities, metals, rates, and net asset values (NAVs), providing data access across both digital and traditional financial asset classes.
What is tick-level price history?
Tick-level price history refers to granular market data that captures individual price movements, providing detailed information about each transaction or price change rather than aggregated data over time intervals.