Crypto Projects MCP Server

An MCP server that provides cryptocurrency project data from Mobula.io to AI agents.

Features

• Fetch Project Data: Retrieve comprehensive project details (e.g., market data, tokenomics, and links) from Mobula.
• Structured Output: Format project data into a well-organized Markdown document with sections for overview, market data, investors, exchanges, token distribution, and release schedules.
• Language Support: Customize output language based on system locale or user-specified settings.

Installation

Prerequisites

• Python 3.10 or higher
• uv for package management and running the project
• Mobula API access (no authentication required for public endpoints)

Setup

1. Clone the Repository:

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

2. Install Dependencies:

   uv sync
   

Usage

Running in Development Mode

Test the server using the MCP Inspector:

uv run mcp dev main.py

Integrating with Claude Desktop

Install the server in Claude Desktop for LLM interaction:

uv run mcp install main.py --name "Crypto Projects"

Example Interaction

The server provides two primary interfaces: a tool to fetch raw data and a prompt to format it into a structured Markdown document.

1. Using the get_project_data Tool

The get_project_data tool retrieves raw JSON data for a specified cryptocurrency project. This is useful for applications needing unprocessed data.

await get_project_data("avalanche")

This returns a dictionary containing details like price, market cap, blockchain, and social links for Avalanche. Example output:

{
  "name": "Avalanche",
  "symbol": "AVAX",
  "blockchains":  ["Avalanche C-Chain"],
  "price": 35.12,
  "market_cap": 1234567890,
  ...
}

2. Using the format_project_data Prompt

The format_project_data prompt fetches data using the get_project_data tool and formats it into a comprehensive Markdown document. This prompt is designed for LLM applications to present structured, human-readable information about a cryptocurrency project.

# format_project_data("avalanche")                 # use system locale
format_project_data("avalanche", lang="en_US")     # use en_US

This generates a Markdown document with detailed sections. Example output for Avalanche:

# Avalanche Project Information

## Overview
- **Name**: Avalanche