Crypto Trending MCP Server
Real-time trending cryptocurrency data via Model Context Protocol tools.
Key Features
Use Cases
README
Crypto Trending MCP Server
An MCP server that tracks and monitors the latest trending tokens on CoinGecko, providing real-time insights into the most popular cryptocurrencies.
Features
-
Tool:
get_trending_md_doc
Returns a Markdown document of the full CoinGecko trending page, including a table of trending cryptocurrencies with columns: Rank, Name, Symbol, Price, 1h Change, 24h Change, 7d Change, 24h Volume, Market Cap. -
Prompt:
parse_trending_md_doc
Guides MCP clients to extract the trending coins table from the Markdown document and parse it with an LLM, supporting analyses like identifying coins with positive price changes or ranking by market cap. -
Seamless Integration
Designed for use with Claude Desktop, allowing natural language queries to analyze trending crypto data via MCP tools and prompts. -
Lightweight & Extensible
Built with minimal dependencies and a simple architecture, making it easy to extend or deploy.
Installation
Prerequisites
- Python 3.10+
- Node.js (for Playwright browser dependencies)
- Claude Desktop (optional, for testing with MCP client)
Steps
-
Clone the Repository:
bashgit clone https://github.com/kukapay/crypto-trending-mcp.git cd crypto-trending-mcp -
Install Dependencies with uv:
bashuv sync playwright install
Usage
Integrating with Claude Desktop
-
Configure Claude Desktop:
-
Edit the configuration file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
- macOS:
-
Add the server configuration:
json{ "mcpServers": { "crypto-trending": { "command": "uv", "args": [ "--directory", "/absolute/path/to/crypto-trending-mcp", "run", "main.py" ] } } }Replace
/absolute/path/to/crypto-trending-mcpwith the absolute path to yourmain.py.
-
-
Restart Claude Desktop:
- Close and reopen Claude Desktop.
- Look for the hammer icon (🔨) in the input box, indicating MCP tools are available.
-
Interact with the Server:
- Ask natural language questions like:
- "What are the trending cryptocurrencies with positive 24h price changes?"
- "Show the top 3 trending coins by market cap."
- Claude will use the
get_trending_md_doctool andparse_trending_md_docprompt to fetch and analyze the data.
- Ask natural language questions like:
Example Output
The get_trending_md_doc tool returns a Markdown document like:
# Trending Crypto
...
| Rank | Name | Symbol | Price | 1h Change | 24h Change | 7d Change | 24h Volume | Market Cap |
|------|-------------|--------|------------|-----------|------------|-----------|-----------------|-------------------|
| 1 | Bitcoin | BTC | $67,890.12 | +0.45% | +2.34% | +10.12% | $45,123,456,789 | $1,345,678,901,234 |
| 2 | Ethereum | ETH | $2,456.78 | -0.12% | -1.12% | +5.67% | $20,987,654,321 | $295,123,456,789 |
| 3 | Solana | SOL | $167.45 | +0.89% | +5.67% | +15.34% | $3,456,789,123 | $78,901,234,567 |
...
*Data from CoinGecko*
The parse_trending_md_doc prompt guides the LLM to extract the table and produce structured output, such as:
[
{
"rank": 1,
"name": "Bitcoin",
"symbol": "BTC",
"price": "$67,890.12",
"change_1h": "+0.45%",
"change_24h": "+2.34%",
"change_7d": "+10.12%",
"volume_24h": "$45,123,456,789",
"market_cap": "$1,345,678,901,234"
},
...
]
License
This project is licensed under the MIT License. See the LICENSE file for details.
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