MCP 服务器

crypto-sentiment-mcp

一个MCP服务器，向AI代理提供加密货币情绪分析。

Tools

get_sentiment_balance

Retrieve the sentiment balance (sentiment_balance_total) for a given asset. Parameters: - asset (str): The cryptocurrency slug (e.g., "bitcoin", "ethereum"). Required. - days (int): Number of days to calculate the average sentiment balance, defaults to 7. Usage: - Use this tool to get the average sentiment balance (positive minus negative sentiment) over a period. Returns: - A string with the average sentiment balance (e.g., "Bitcoin's sentiment balance over the past 7 days is 12.5").

get_social_volume

Retrieve the total social volume (social_volume_total) for a given asset. It calculates the total number of social data text documents that contain the given search term at least once. Examples of documents are telegram messages and reddit posts. Parameters: - asset (str): The cryptocurrency slug (e.g., "bitcoin", "ethereum"). Required. - days (int): Number of days to sum the social volume, defaults to 7. Usage: - Call this tool to get the total number of social media mentions for an asset over a period. Returns: - A string with the total social volume (e.g., "Bitcoin's social volume over the past 7 days is 15,000 mentions").

alert_social_shift

Detect significant shifts (spikes or drops) in social volume (social_volume_total) for a given asset. Parameters: - asset (str): The cryptocurrency slug (e.g., "bitcoin", "ethereum"). Required. - threshold (float): Minimum percentage change (absolute value) to trigger an alert, defaults to 50.0 (i.e., 50%). - days (int): Number of days to analyze for baseline volume, defaults to 7. Usage: - Call this tool to check if the latest social volume has significantly spiked or dropped compared to the previous average. Returns: - A string indicating if a shift occurred (e.g., "Bitcoin's social volume spiked by 75.0% in the last 24 hours" or "Bitcoin's social volume dropped by 60.0% in the last 24 hours").

get_trending_words

Retrieve the top trending words in the crypto space over a specified period, aggregated and ranked by score. Parameters: - days (int): Number of days to analyze trending words, defaults to 7. - top_n (int): Number of top trending words to return, defaults to 5. Usage: - Call this tool to get a list of the most popular words trending in cryptocurrency discussions, ranked across the entire period. Returns: - A string listing the top trending words (e.g., "Top 5 trending words over the past 7 days: 'halving', 'bullrun', 'defi', 'nft', 'pump'").

get_social_dominance

Retrieve the social dominance (social_dominance_total) for a given asset. Social Dominance shows the share of the discussions in crypto media that is referring to a particular asset or phrase. Parameters: - asset (str): The cryptocurrency slug (e.g., "bitcoin", "ethereum"). Required. - days (int): Number of days to calculate average social dominance, defaults to 7. Usage: - Call this tool to get the percentage of social media discussion dominated by the asset. Returns: - A string with the average social dominance (e.g., "Bitcoin's social dominance over the past 7 days is 25.3%").

README

加密货币情绪 MCP 服务器

一个 MCP 服务器，为 AI 代理提供加密货币情绪分析，利用 Santiment 聚合的社交媒体和新闻数据来跟踪市场情绪并检测新兴趋势。

GitHub 许可证

功能

情绪分析: 获取特定加密货币的情绪平衡（正面与负面）。
社交量跟踪: 监控社交媒体提及的总量，并检测到显著的变化（峰值或下降）。
社交主导性: 衡量一种资产在加密货币媒体讨论中所占的份额。
热门词汇: 识别加密货币讨论中最流行的趋势词汇。

工具

工具名称	描述	参数
`get_sentiment_balance`	获取资产在指定时期内的平均情绪平衡。	`asset: str`, `days: int = 7`
`get_social_volume`	获取资产的社交媒体提及总数。	`asset: str`, `days: int = 7`
`alert_social_shift`	检测与先前平均值相比，社交量的显著峰值或下降。	`asset: str`, `threshold: float = 50.0`, `days: int = 7`
`get_trending_words`	检索加密货币讨论中最热门的词汇，按一段时间内的得分排名。	`days: int = 7`, `top_n: int = 5`
`get_social_dominance`	衡量一种资产在加密货币媒体讨论中所占的百分比。	`asset: str`, `days: int = 7`

前提条件

Python: 3.10 或更高版本
Santiment API 密钥: 从 Santiment 获取免费或付费密钥。

安装

克隆存储库:

git clone https://github.com/kukapay/crypto-sentiment-mcp.git
cd crypto-sentiment-mcp

配置客户端:

{
  "mcpServers": {
    "crypto-sentiment-mcp": {
      "command": "uv",
      "args": ["--directory", "path/to/crypto-sentiment-mcp", "run", "main.py"],
      "env": {
        "SANTIMENT_API_KEY": "your_api_key_here"
      }
    }
  }
}

示例

以下是通过 MCP 兼容客户端与服务器交互时，自然语言输入及其相应输出的示例：

输入: "过去一周比特币的情绪平衡是多少？"
- 输出: "过去 7 天比特币的情绪平衡为 12.5。"
输入: "过去 5 天以太坊在社交媒体上被提及了多少次？"
- 输出: "过去 5 天以太坊的社交量为 8,432 次提及。"
输入: "告诉我最近比特币的社交量是否有重大变化，阈值为 30%。"
- 输出: "在过去 24 小时内，比特币的社交量飙升了 75.0%，从平均 1,000 次增加到 1,750 次。"
输入: "过去 3 天加密货币中最热门的 3 个词是什么？"
- 输出: "过去 3 天最热门的 3 个词：'减半'、'牛市'、'defi'。"
输入: "本周以太坊在社交媒体讨论中的主导地位如何？"
- 输出: "过去 7 天以太坊的社交主导性为 18.7%。"