Surf MCP Server
Enables access to 86 crypto data endpoints from the Surf API, including market data, wallets, social sentiment, on-chain queries, and more, through dynamically generated MCP tools.
README
surf-mcp
MCP server for the Surf crypto data API. Dynamically generates tools from the OpenAPI spec — 12 grouped tools covering 86 endpoints across market data, wallets, social, on-chain queries, and more.
Quick start
Add to your MCP client config — no clone or install needed:
{
"mcpServers": {
"surf": {
"command": "npx",
"args": ["-y", "@surf-ai/surf-mcp"],
"env": {
"SURF_API_KEY": "your-api-key"
}
}
}
}
Or with Bun:
{
"mcpServers": {
"surf": {
"command": "bunx",
"args": ["@surf-ai/surf-mcp"],
"env": {
"SURF_API_KEY": "your-api-key"
}
}
}
}
Prerequisites
- A Surf API key (get one here)
- Node.js 20+ or Bun
Config file locations
- Claude Code:
.mcp.jsonin project root or~/.claude.json - Claude Desktop:
~/Library/Application Support/Claude/claude_desktop_config.json(macOS) - Cursor: MCP settings in the IDE
Tools
The server exposes 12 tools, one per API domain. Each tool accepts a command and optional params:
| Tool | Commands | Description |
|---|---|---|
surf_market |
price, ranking, etf, futures, options, fear-greed, liquidation-*, onchain-indicator, price-indicator |
Market overview, rankings, indicators, ETF flows |
surf_exchange |
depth, klines, funding-history, perp, price, markets, long-short-ratio |
Live exchange data from Binance, OKX, Bybit, etc. |
surf_wallet |
detail, transfers, history, net-worth, protocols, labels-batch |
Wallet balances, transfers, DeFi positions |
surf_token |
holders, dex-trades, transfers, tokenomics |
Token holder analysis, DEX trades, unlocks |
surf_social |
detail, user, user-posts, tweets, mindshare, ranking, smart-followers-history, tweet-replies, user-followers, user-following, user-replies |
X (Twitter) social signals and sentiment |
surf_project |
detail, defi-metrics, defi-ranking |
Project profiles, DeFi TVL/fees/revenue |
surf_onchain |
sql, tx, gas-price, schema, bridge-ranking, yield-ranking, structured-query |
On-chain SQL queries, tx lookup, gas prices |
surf_search |
project, wallet, news, web, fund, polymarket, kalshi, airdrop, events, social-people, social-posts |
Unified search across all data types |
surf_prediction_market |
kalshi-*, polymarket-*, matching-*, category-metrics |
Polymarket and Kalshi prediction markets |
surf_fund |
detail, portfolio, ranking |
Crypto VC fund profiles and portfolios |
surf_news |
feed, detail |
Crypto news from major outlets |
surf_web |
fetch |
Fetch any URL as clean markdown |
Usage examples
Once configured, your AI assistant can use the tools directly:
"What's the BTC price?" → surf_market({ command: "price", params: { symbol: "BTC" } })
"Check vitalik's wallet" → surf_wallet({ command: "detail", params: { address: "vitalik.eth" } })
"Search for DeFi projects" → surf_search({ command: "project", params: { q: "defi lending" } })
"Run an on-chain SQL query" → surf_onchain({ command: "sql", params: { sql: "SELECT ..." } })
"ETH social sentiment" → surf_social({ command: "detail", params: { q: "ethereum" } })
How it works
On startup, the server:
- Fetches the OpenAPI spec from
https://api.asksurf.ai/gateway/openapi.json(cached for 24h) - Groups all operations by their API tag
- Registers one MCP tool per tag with auto-generated descriptions and command enums
- Routes tool calls through
@surf-ai/sdkfor HTTP transport and auth
The server automatically picks up new API endpoints when the spec is updated — just restart.
Example: AI agent
The repo includes a simple agent that connects Claude to surf-mcp tools in an agentic loop. See examples/agent.ts.
ANTHROPIC_API_KEY=your-key SURF_API_KEY=your-key bun run examples/agent.ts "What's the BTC price and fear & greed index?"
Development
git clone https://github.com/asksurf-ai/surf-mcp.git
cd surf-mcp
bun install
bun run start # Run the server
bun run typecheck # Type check
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。