Funding-mcp
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Alternatives to Funding-mcp
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AlicenseAqualityFmaintenancePerp-first funding rate & RWA spread data for AI agents. 30+ CEX/DEX venues, 6 tools (4 x402-paywalled, 2 free), bring-your-own-wallet via Base mainnet.61MIT- AlicenseAqualityAmaintenancePay-per-call ($0.005-$0.03 USDC) market and on-chain data API for AI agents and trading bots via the x402 protocol — no signup, no API key. Exposed as a remote MCP server with 12 tools — one free onboarding tool (dump-risk), the rest pay-per-call (kimchi premium, funding rate APR, DEX slippage, token security, arbitrage spread, and more).414MIT
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- AlicenseAqualityCmaintenanceReal-time crypto intelligence for AI agents. Technical analysis, liquidation heatmaps, sentiment, and funding rates for 50+ Hyperliquid perpetuals via x402 micropayments.1556 PyPI1MIT

hyperd-mcpofficial
AlicenseAqualityCmaintenancePre-trade DeFi intelligence for AI agents. 20 paid x402 endpoints, USDC on Base.2329 npm1MIT- FlicenseAqualityDmaintenancePay-per-call tools for AI agents including trust checks, due diligence, market data, and human-verified approvals, settled in USDC on Base via the x402 protocol.16-
TDQS
Scored across 12 tools
Each tool targets a distinct aspect of perpetual funding market data: arbitrage screening, history, signal, spread, open interest, volume, orderbook, etc. Even closely related tools like funding_arb and funding_signal have clear differences in scope and detail.
All tool names follow a consistent lowercase_snake_case pattern, primarily noun_noun (e.g., funding_arb, volume_24h) or adjective_noun (e.g., open_interest). The naming is predictable and descriptive, with no mixed conventions.
With 12 tools, the server offers a well-scoped set that covers the core domain without being overwhelming or too sparse. Each tool earns its place by addressing a specific data need.
The tool surface covers key areas of perpetual funding analysis: funding rates (history, spread, signal, screen), open interest, volume, orderbook slippage, oracle risk, and RWA coverage. There are no obvious gaps for the intended use case of market data retrieval and analysis.