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Awesome Crypto MCP Servers

MCP Server

Curated crypto-focused Model Context Protocol servers for AI integration

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Updated 21 days ago

About

A curated collection of MCP server implementations that provide on-chain data, token analytics, transaction history, and real‑time crypto market information. Designed for developers and AI agents to access blockchain data securely and efficiently.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Overview of the Awesome Crypto MCP Servers Collection

The Awesome Crypto MCP Servers project is a curated catalogue of Model Context Protocol (MCP) servers that bring real‑world cryptocurrency data and blockchain interactions into AI assistants. It addresses a core pain point for developers: the difficulty of connecting language models to live financial markets, on‑chain state, and specialized analytics without building custom adapters. By exposing a standardized set of resources, tools, and prompts, each server lets an AI agent fetch market prices, submit transactions, or analyze smart‑contract behavior with a single, well‑defined call. This streamlines workflow pipelines where an assistant must answer user queries about token prices, execute trades, or monitor whale movements in real time.

The collection covers a broad spectrum of use cases. Some servers, like coin_api_mcp and DexPaprika, provide high‑frequency market data for over five million tokens across dozens of blockchains, enabling portfolio tracking or automated trading bots. Others, such as bankless/onchain-mcp and EVM MCP Server, expose on‑chain queries—ERC20 balances, transaction histories, ENS resolution—so an assistant can verify ownership or audit smart‑contract state on the fly. Transactional servers like magnetai/mcp-free-usdc-transfer demonstrate how an AI can initiate token transfers on Base using Coinbase’s MPC wallet, eliminating manual steps for users.

Key capabilities across the servers include:

  • Real‑time market feeds: instant price quotes, liquidity pools, and DEX analytics.
  • Historical data access: time‑series queries for backtesting strategies or generating reports.
  • On‑chain querying and execution: read/write operations on EVM, Solana, Base, and other networks.
  • News & sentiment: integration with CryptoPanic for up‑to‑date headlines and the Fear & Greed Index.
  • Specialized analytics: whale tracking, smart‑contract security checks via Heurist Mesh agents.

These features make the collection invaluable for developers building AI‑powered fintech tools, automated trading platforms, or compliance dashboards. An assistant can answer a user’s question about the latest price of Solana, fetch its recent whale trades, and even execute a transaction—all through a single MCP call chain. The standardized interface also allows for easy swapping of back‑ends; if one data source goes down, a different MCP server can fill the gap without changing application logic.

In practice, a typical workflow might involve an AI assistant receiving a user request like “Show me the top 10 liquid tokens on Solana and transfer $500 worth to my wallet.” The assistant would use the DexPaprika server to pull liquidity data, Solana Agent Kit to fetch token prices, and the EVM MCP Server (or a Solana‑specific server) to submit the transfer. The seamless integration of these MCP servers into the assistant’s prompt engine means developers can focus on business logic rather than protocol plumbing, accelerating time‑to‑market for crypto‑centric AI applications.