Maiga API MCP Server

A Model Context Protocol (MCP) server that provides comprehensive integration with the Maiga API for cryptocurrency analysis, including token analysis, market reports, KOL insights, and trending token discovery.

Overview

This MCP server enables AI assistants and applications to interact with Maiga's cryptocurrency analysis platform through a standardized protocol. It provides access to technical and fundamental analysis, social sentiment analysis, token holder information, market reports, KOL (Key Opinion Leader) analytics, and trending token discovery.

Features

Available Tools

• Token Analysis (maiga_analyse_token) - Performs comprehensive technical and fundamental analysis on cryptocurrency tokens

• Mindshare Analysis (maiga_mindshare) - Analyzes social media sentiment and trending discussions about tokens over the last 24 hours

• Token Information (maiga_token_info) - Retrieves detailed token holder information and on-chain analysis

• Market Reports (maiga_market_report) - Generates specialized market reports (Market Behavior, Open Interest, Multi-Timeframe, Fund Flow)

• KOL Analysis (maiga_kol_analysis) - Analyzes the influence and statistics of cryptocurrency influencers on X (Twitter)

• Trending Tokens (maiga_trending_tokens) - Retrieves top trending tokens in the last 24 hours based on social media mentions and activity

Prerequisites

• Node.js (v16 or higher)

• npm, yarn, pnpm, or bun

• Maiga Partner API token (contact your account manager to obtain)

Installation

1. Clone the repository:

2. Install dependencies:

3. Obtain a Maiga Partner API token:

   • Contact your Maiga account manager to obtain your partner API token

   • Keep your API token secure and ready for configuration

Configuration

The server requires the following configuration:

• apiToken (required): Your Maiga Partner API token for authentication

Configuration Methods

1. Smithery Playground (Development)

When running npm run dev, the Smithery Playground will open in your browser. Enter your apiToken in the configuration section.

2. URL Parameters (Testing)

When connecting via HTTP, pass configuration as URL query parameters:

3. Production Configuration

Once deployed to Smithery, users can securely manage their configurations through the configuration UI. Saved configurations are automatically applied when connecting to the server.

Development

Start the development server:

This will:

• Start the MCP server on port 8081 (or custom port with --port flag)

• Enable hot reloading

• Open the Smithery Playground in your browser for testing

Build

Build for production:

Creates a bundled server in .smithery/ directory.

Usage

With MCP-Compatible Applications

This server can be used with any application that supports the Model Context Protocol, such as:

• Claude Desktop

• MCP-enabled IDEs

• Custom MCP clients

• Smithery Playground

Tool Examples

Analyze a token:

Get mindshare analysis:

Get token holder information:

Generate market report:

Analyze a KOL:

Get trending tokens:

API Reference

Token Operations

• maiga_analyse_token(identifier) - Comprehensive token analysis

  • Parameters:

    • identifier (string, required): Token symbol (e.g., "bitcoin", "ethereum", "BTC") or contract address

  • Returns: Technical analysis, price data, market cap, links, and analysis text

• maiga_mindshare(identifier) - Social media sentiment analysis

  • Parameters:

    • identifier (string, required): Token symbol or contract address

  • Returns: Social sentiment analysis and trending discussions from the last 24 hours

• maiga_token_info(identifier) - Token holder and on-chain analysis

  • Parameters:

    • identifier (string, required): Token contract address or identifier

  • Returns: Top holders, holder distribution analysis, and token information

Market Analysis

• maiga_market_report(mode) - Generate market reports

  • Parameters:

    • mode (enum, required): Analysis mode

      • "Market_Behavior" - Overall market sentiment and behavior patterns

      • "Open_Interest" - Futures and derivatives open interest analysis

      • "Multi_Timeframe" - Multi-timeframe technical analysis

      • "Fund_Flow" - Capital flow and whale movement analysis

  • Returns: Mode-specific market analysis data

Social & Influencer Analysis

• maiga_kol_analysis(username) - KOL influence analysis

  • Parameters:

    • username (string, required): Twitter username without @ symbol (e.g., "cz_binance")

  • Returns: Follower count, engagement metrics, reach statistics, and influence analysis

• maiga_trending_tokens() - Get trending tokens

  • Parameters: None

  • Returns: Top trending tokens from the last 24 hours with mentions, sentiment, and trend data

Rate Limiting

The Maiga API enforces rate limiting:

• Limit: 1000 requests per hour per IP address

• Window: 3600 seconds (1 hour)

If you exceed the rate limit, you will receive a 429 Too Many Requests response with information about when you can retry. The server handles rate limit errors gracefully and provides clear error messages.

Error Handling

The server includes comprehensive error handling for:

• API authentication failures (401 Unauthorized)

• Invalid request parameters (400 Bad Request)

• Rate limit exceeded (429 Too Many Requests)

• Network connectivity issues

• Invalid parameter validation

• Maiga API errors (500 Internal Server Error)

All errors are returned as structured responses with descriptive messages. Rate limit errors include retry-after information.

Security

• API tokens are required and validated at connection time

• All requests use HTTPS

• Input validation using Zod schemas

• No sensitive data is logged in production

• API tokens should never be exposed in client-side code or public repositories

Tech Stack

• Runtime: TypeScript

• MCP SDK: @modelcontextprotocol/sdk

• HTTP Client: Native fetch API

• Validation: Zod

• Development: Smithery CLI

• Build Tool: Smithery Build

Project Structure

Deploy

Ready to deploy? Push your code to GitHub and deploy to Smithery:

1. Create a new repository at github.com/new

2. Initialize git and push to GitHub:

   git add . git commit -m "Initial commit" git remote add origin https://github.com/YOUR_USERNAME/YOUR_REPO.git git push -u origin main

3. Deploy your server to Smithery at smithery.ai/new

Contributing

1. Fork the repository

2. Create a feature branch

3. Make your changes

4. Add tests if applicable

5. Submit a pull request

License

ISC

Support

For issues related to:

• This MCP Server: Create an issue in this repository

• Maiga API: Contact your Maiga account manager

• Model Context Protocol: Visit MCP Documentation

• Smithery: Visit Smithery Documentation

Learn More

• Smithery Docs

• MCP Protocol

• Session Config Documentation

Changelog

v1.0.0

• Initial release with full Maiga API integration

• Support for all 6 Maiga API endpoints:

  • Token Analysis

  • Mindshare Analysis

  • Token Information

  • Market Reports

  • KOL Analysis

  • Trending Tokens

• Comprehensive error handling and validation

• Rate limit handling

• Full TypeScript type safety