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pythia-the-oracle/pythia-oracle-mcp

by Various

Every smart contract deserves intelligence, not just data. MCP server for on-chain calculated indicators (EMA, RSI, VWAP, Bollinger, volatility) via Chainlink.

P

MCP

pythia-the-oracle/pythia-oracle-mcp

Added 1 June 2026

#ai-agent #chainlink #crypto #defi #indicators #mcp-server #model-context-protocol #on-chain

Overview

An MCP server that calculates on-chain technical indicators (EMA, RSI, VWAP, Bollinger Bands, volatility) using Chainlink data feeds. It provides smart contracts with derived intelligence rather than raw price data.

Best for

Best for
Smart contract developers who need on-chain technical analysis indicators for DeFi protocols.

Use cases

  • Incorporate RSI or EMA into DeFi trading strategies directly in smart contracts
  • Compute on-chain volatility for risk management or derivative pricing
  • Add Bollinger Band signals to automated market maker or lending protocols

Notes

An MCP server that calculates on-chain technical indicators (EMA, RSI, VWAP, Bollinger Bands, volatility) using Chainlink data feeds. It provides smart contracts with derived intelligence rather than raw price data.

0 stars on GitHub. Last updated 2026-05-26. Licensed MIT.

Use cases

  • Incorporate RSI or EMA into DeFi trading strategies directly in smart contracts
  • Compute on-chain volatility for risk management or derivative pricing
  • Add Bollinger Band signals to automated market maker or lending protocols

Pros

  • Delivers calculated indicators on-chain, reducing off-chain dependency
  • Leverages Chainlink for reliable, decentralized price data
  • Python implementation makes it accessible to a wide developer audience

Cons

  • Depends on Chainlink infrastructure and its data availability
  • Limited to the specified indicators without built-in extensibility
  • No community traction (0 stars) indicating early stage or low adoption

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Delivers calculated indicators on-chain, reducing off-chain dependency
  • Leverages Chainlink for reliable, decentralized price data
  • Python implementation makes it accessible to a wide developer audience

Cons

  • Depends on Chainlink infrastructure and its data availability
  • Limited to the specified indicators without built-in extensibility
  • No community traction (0 stars) indicating early stage or low adoption
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