Tuatara Embed Stocks
Stock-symbol vectors: which listed symbols an event, theme or headline moves, ranked in one call.
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质量与安全性
基于对工具定义和协议合规性的自动分析。
上下文开销
这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高，可用于其他任务的注意力就越少。
安装
一键安装
将以下内容添加到你的 `claude_desktop_config.json` 文件中：
{
"mcpServers": {
"tuatara-embed-stocks": {
"url": "https://cymetica.com/mcp/v1/stock-vectors"
}
}
}远程端点
https://cymetica.com/mcp/v1/stock-vectorsstreamable-http它能做什么
工具清单
工具（1）
🟢stock_vectors(input, encoding_format, similarity_to_first)
Tuatara Embed Stocks: vector embeddings of listed stock symbols and of text in one space, built for the connections a sector label does not carry — which symbols an event, theme or headline moves, including companies it never names. Send sym:TICKER (e.g. sym:AAPL) for a symbol's own vector, or any text (a headline, a theme). With similarity_to_first=true the answer ranks inputs 2..n by cosine to input 1, so 'headline + candidate symbols in, ranked basket out' is one call. 4,096 dimensions, unit length. Up to 64 inputs per call; no account needed; nothing is stored.
输入模式
{
"type": "object",
"properties": {
"input": {
"type": "array",
"description": "list of texts to embed: sym:TICKER for a listed symbol's own vector, anything else is embedded as text; at most 64"
},
"encoding_format": {
"type": "string",
"description": "base64 (default, float32 little-endian) or float (4,096 numbers)"
},
"similarity_to_first": {
"type": "boolean",
"description": "also return every other input's cosine to the first input, ranked (e.g. first = the headline, the rest = candidate symbols)"
}
},
"required": [
"input"
]
}社区
证据