What tool does Signalmelo Mcp provide?
It provides exactly one tool: `analyze_reddit_community_signals`.

@carter-wzq
基本信息
A lightweight BYOK MCP server for Reddit community signal analysis. It returns structured outputs for What Users Like, What Users Don't Like, and Competitors Users Mention from Reddit discussions.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"signalmelo-mcp": {
"command": "node",
"args": [
"<ABSOLUTE_PATH>/signalmelo-mcp/dist/index.js"
],
"env": {
"REDDIT_CLIENT_ID": "<YOUR_REDDIT_CLIENT_ID>",
"REDDIT_CLIENT_SECRET": "<YOUR_REDDIT_CLIENT_SECRET>",
"REDDIT_USER_AGENT": "signalmelo-mcp/0.1 by your_reddit_username",
"LLM_API_KEY": "<YOUR_LLM_API_KEY>"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Signalmelo Mcp is a lightweight MCP server that analyzes Reddit communities for user signals. It provides a single tool, analyze_reddit_community_signals, which extracts what users like, dislike, and which competitors they mention, along with source links. It is intended for developers and product teams who want to gather qualitative feedback from Reddit.
Install dependencies with npm install and build the project with npm run build. Configure your own Reddit API and LLM API keys as environment variables, then add the server to your MCP client configuration with the command node <ABSOLUTE_PATH>/signalmelo-mcp/dist/index.js. Invoke the tool with a query, a list of subreddits (max 5), a time range, and a max posts count (5–50).
It provides exactly one tool: `analyze_reddit_community_signals`.
You need a Reddit client ID, secret, and user agent, plus an LLM API key. These are set as environment variables `REDDIT_CLIENT_ID`, `REDDIT_CLIENT_SECRET`, `REDDIT_USER_AGENT`, and `LLM_API_KEY`.
Go to Reddit app preferences (https://www.reddit.com/prefs/apps), create a "script" app, fill in the required fields, and copy the client ID and secret.
The `subreddits` array has a maximum length of 5, and `maxPosts` must be between 5 and 50.
The tool still returns `sources` as a fallback, even if summarization fails.

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