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This library provides convenient way to use Coinpaprika.com API in Python.
Public SDK, CLI, and docs for Hive Intelligence: crypto MCP access for AI agents.
Noise Framework implementation in Zig Language for use in EVER/IP and WireGuard
Blockchain for a record management and money transfer system
Official DexPaprika Python SDK: Pythonic access to cross-chain DEX data, prices, and pools with type hints and caching.
MCP server for real-time news with bias scoring, live stock/ETF/crypto data, AI options pricing, balanced news synthesis, and meme search. 10 tools, 5000+ sources, free tier.
63 deterministic quant computation tools for autonomous financial agents. Options, derivatives, risk, portfolio, statistics, crypto/DeFi, macro/FX, TVM. 1,000 free calls/day — no signup.
EVM blockchain intelligence toolkit for AI agents — 23 MCP tools across 7 chains (Ethereum, Polygon, Arbitrum, Base, Optimism, Avalanche, BSC). Zero config.
x402 protocol API server — pay-per-call DeFi data endpoints using USDC micropayments on Base
MCP server for DeFi execution — lets AI agents swap, provide liquidity, lend, bridge, and run yield strategies across 22 chains
ZeiCoin is a minimalist cryptocurrency blockchain written in Zig with cumulative proof-of-work consensus, CPU mining and peer-to-peer networking.
Simple Python SDK for the CoinPulse crypto portfolio API. No OAuth, no complex setup.
MCP server for Verilex Data — query NPI, SEC, PACER, Weather, and OTC datasets from AI agents
MCP server for Gloria AI — real-time curated crypto news with sentiment, recaps, and search for AI agents
Official MCP server for Horus Flow Intelligence: Institutional-grade market microstructure and orderflow physics for AI trading agents.
MCP server for Marcus Rug Intel — 19 tools for crypto token risk analysis, rug pull detection, and AI forensics. Works with Claude Desktop, Cursor, Windsurf.
MCP-Server für Solana-Blockchain-Daten — Wallets, Token-Preise, DeFi-Yields, Sicherheitschecks
macOS native voice input for Crypto + AI professionals — offline ASR, domain vocabulary, implicit learning