Crypto Trending MCP Server
@kukapay
About Crypto Trending MCP Server
An MCP server that tracks and monitors the latest trending tokens on CoinGecko.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"crypto-trending-mcp": {
"command": "uv",
"args": [
"sync"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Crypto Trending MCP Server?
Crypto Trending MCP Server tracks and monitors the latest trending tokens on CoinGecko, providing real-time insights into the most popular cryptocurrencies. It is designed for developers and crypto enthusiasts who want to analyze trending market data through natural language queries using MCP-compatible clients like Claude Desktop.
How to use Crypto Trending MCP Server?
Install with uv sync and playwright install, then configure Claude Desktop by adding the server as an MCP tool in claude_desktop_config.json. Once connected, ask natural language questions such as “What are the trending cryptocurrencies with positive 24h price changes?” – Claude will fetch and analyze the data using the built-in tool and prompt.
Key features of Crypto Trending MCP Server
- Tool:
get_trending_md_docreturns a Markdown table of trending cryptocurrencies. - Prompt:
parse_trending_md_docguides LLM to extract and parse the table. - Designed for seamless integration with Claude Desktop.
- Lightweight and extensible with minimal dependencies.
- Powered by real‑time CoinGecko trending data.
- Supports analysis by price changes, volume, and market cap.
Use cases of Crypto Trending MCP Server
- Identify which trending cryptocurrencies have positive 24‑hour price changes.
- Rank the top 3 trending coins by market cap.
- Retrieve a structured JSON list of trending tokens for further analysis.
- Monitor market momentum with real‑time CoinGecko data via natural language queries.
FAQ from Crypto Trending MCP Server
What does the Crypto Trending MCP Server do?
It fetches and returns a Markdown document of the full CoinGecko trending page, including a table with rank, name, symbol, price, 1h/24h/7d changes, 24h volume, and market cap for trending cryptocurrencies.
What are the prerequisites to run it?
Python 3.10+, Node.js (for Playwright browser dependencies), and optionally Claude Desktop for testing with an MCP client.
How do I integrate it with Claude Desktop?
Edit the Claude Desktop config file (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json, Windows: %APPDATA%\Claude\claude_desktop_config.json) and add the server configuration with uv pointing to main.py, then restart Claude Desktop.
What data does the server return?
The get_trending_md_doc tool returns a Markdown table; the parse_trending_md_doc prompt guides the LLM to extract that table into a structured JSON array with fields like rank, name, symbol, price, and changes.
Are there any known limitations?
The server relies on Playwright browser dependencies and an active CoinGecko connection. It is designed for use with MCP clients and requires a working Python/Node environment.
Frequently asked questions
What does the Crypto Trending MCP Server do?
It fetches and returns a Markdown document of the full CoinGecko trending page, including a table with rank, name, symbol, price, 1h/24h/7d changes, 24h volume, and market cap for trending cryptocurrencies.
What are the prerequisites to run it?
Python 3.10+, Node.js (for Playwright browser dependencies), and optionally Claude Desktop for testing with an MCP client.
How do I integrate it with Claude Desktop?
Edit the Claude Desktop config file (macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`, Windows: `%APPDATA%\Claude\claude_desktop_config.json`) and add the server configuration with `uv` pointing to `main.py`, then restart Claude Desktop.
What data does the server return?
The `get_trending_md_doc` tool returns a Markdown table; the `parse_trending_md_doc` prompt guides the LLM to extract that table into a structured JSON array with fields like rank, name, symbol, price, and changes.
Are there any known limitations?
The server relies on Playwright browser dependencies and an active CoinGecko connection. It is designed for use with MCP clients and requires a working Python/Node environment.
Basic information
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