ai-mldeveloper-tools

Ultra (Multi-AI Provider)

realmikechong

by realmikechong

Ultra (Multi-AI Provider) unifies OpenAI, Gemini, and Azure models, tracking usage, estimating costs, and offering 9 dev

Unified server providing access to OpenAI O3, Google Gemini 2.5 Pro, and Azure OpenAI models with automatic usage tracking, cost estimation, and nine specialized development tools for code analysis, debugging, and documentation generation.

github stars

268

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Zero setup with npx ultra-mcpBuilt-in web dashboardLocal usage analytics

best for

  • / Developers using Claude or Cursor who need multiple AI models
  • / Teams wanting to compare outputs across different LLMs
  • / Projects requiring cost tracking for AI usage

capabilities

  • / Query OpenAI O3 and GPT models
  • / Access Google Gemini 2.5 Pro
  • / Use Azure OpenAI services
  • / Track token usage and costs automatically
  • / Generate code documentation
  • / Analyze and debug code

what it does

Provides access to OpenAI O3, Google Gemini 2.5 Pro, and Azure OpenAI models through a single interface with built-in usage tracking and cost estimation.

about

Ultra (Multi-AI Provider) is a community-built MCP server published by realmikechong that provides AI assistants with tools and capabilities via the Model Context Protocol. Ultra (Multi-AI Provider) unifies OpenAI, Gemini, and Azure models, tracking usage, estimating costs, and offering 9 dev It is categorized under ai ml, developer tools.

how to install

You can install Ultra (Multi-AI Provider) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Ultra (Multi-AI Provider) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Ultra MCP

All Models. One Interface. Zero Friction.

npm version npm downloads

🚀 Ultra MCP - A Model Context Protocol server that exposes OpenAI, Gemini, Azure OpenAI, and xAI Grok AI models through a single MCP interface for use with Claude Code and Cursor.

img

Stop wasting time having meetings with human. Now it's time to ask AI models do this.

Inspiration

This project is inspired by:

  • Agent2Agent (A2A) by Google - Thank you Google for pioneering agent-to-agent communication protocols
  • Zen MCP - The AI orchestration server that enables Claude to collaborate with multiple AI models

Why Ultra MCP?

While inspired by zen-mcp-server, Ultra MCP offers several key advantages:

🚀 Easier to Use

  • No cloning required - Just run npx ultra-mcp to get started
  • NPM package - Install globally with npm install -g ultra-mcp
  • Interactive setup - Guided configuration with npx ultra-mcp config
  • Zero friction - From zero to AI-powered coding in under a minute

📊 Built-in Usage Analytics

  • Local SQLite database - All usage data stored locally using libSQL
  • Automatic tracking - Every LLM request is tracked with token counts and costs
  • Usage statistics - View your AI usage with npx ultra-mcp db:stats
  • Privacy first - Your data never leaves your machine

🌐 Modern Web Dashboard

  • Beautiful UI - React dashboard with Tailwind CSS
  • Real-time stats - View usage trends, costs by provider, and model distribution
  • Easy access - Just run npx ultra-mcp dashboard
  • Configuration UI - Manage API keys and model priorities from the web

🔧 Additional Benefits

  • Simplified tools - Maximum 4 parameters per tool (vs zen's 10-15)
  • Smart defaults - Optimal model selection out of the box
  • TypeScript first - Full type safety and better developer experience
  • Regular updates - Active development with new features weekly

Features

  • 🤖 Multi-Model Support: Integrate OpenAI (GPT-5), Google Gemini (2.5 Pro), Azure OpenAI, and xAI Grok models
  • 🔌 MCP Protocol: Standard Model Context Protocol interface
  • 🎯 Discoverable Prompts: All 25 tools available as prompts in Claude Code (New in v0.7.0)
  • 🧠 Deep Reasoning Tools: Access GPT-5 for complex problem-solving
  • 🔍 Investigation & Research: Built-in tools for thorough investigation and research
  • 🌐 Google Search Integration: Gemini 2.5 Pro with real-time web search
  • Real-time Streaming: Live model responses via Vercel AI SDK
  • 🔧 Zero Config: Interactive setup with smart defaults
  • 🔑 Secure Configuration: Local API key storage with conf library
  • 🧪 TypeScript: Full type safety and modern development experience

Quick Start

Installation

# Install globally via npm
npm install -g ultra-mcp

# Or run directly with npx
npx -y ultra-mcp config

Configuration

Set up your API keys interactively:

npx -y ultra-mcp config

This will:

  1. Show current configuration status
  2. Present a provider-first menu to select which AI provider to configure
  3. Guide you through setting API keys, base URLs, and preferred models
  4. Store configuration securely on your system
  5. Auto-load settings when the server starts

New in v0.5.10:

  • 🎯 Provider-first configuration - Select specific provider to configure
  • 🤖 OpenAI-Compatible support - Configure Ollama (local) or OpenRouter (400+ models)
  • 📋 Model selection - Choose your preferred model from categorized lists

Running the Server

# Run the MCP server
npx -y ultra-mcp

# Or after building locally
bun run build
node dist/cli.js

CLI Commands

Ultra MCP provides several powerful commands:

config - Interactive Configuration

npx -y ultra-mcp config

Configure API keys interactively with a user-friendly menu system.

dashboard - Web Dashboard

npx -y ultra-mcp dashboard

# Custom port
npx -y ultra-mcp dashboard --port 4000

# Development mode
npx -y ultra-mcp dashboard --dev

Launch the web dashboard to view usage statistics, manage configurations, and monitor AI costs.

install - Install for Claude Code

npx -y ultra-mcp install

Automatically install Ultra MCP as an MCP server for Claude Code.

doctor - Health Check

npx -y ultra-mcp doctor

# Test connections to providers
npx -y ultra-mcp doctor --test

Check installation health and test API connections.

chat - Interactive Chat

npx -y ultra-mcp chat

# Specify model and provider
npx -y ultra-mcp chat -m gpt-5 -p openai
npx -y ultra-mcp chat -m grok-4 -p grok

Chat interactively with AI models from the command line.

Database Commands

db:show - Show Database Info

npx -y ultra-mcp db:show

Display database file location and basic statistics.

db:stats - Usage Statistics

npx -y ultra-mcp db:stats

Show detailed usage statistics for the last 30 days including costs by provider.

db:view - Database Viewer

npx -y ultra-mcp db:view

Launch Drizzle Studio to explore the usage database interactively.

Integration with Claude Code

Automatic Installation (Recommended)

# Install Ultra MCP for Claude Code
npx -y ultra-mcp install

This command will:

  • Detect Claude Code installation
  • Add Ultra MCP as an MCP server
  • Configure for user or project scope
  • Verify API key configuration

Manual Installation

Add to your Claude Code settings:

{
  "mcpServers": {
    "ultra-mcp": {
      "command": "npx",
      "args": ["-y", "ultra-mcp@latest"]
    }
  }
}

Integration with Cursor

First configure your API keys:

npx -y ultra-mcp config

Then add to your Cursor MCP settings:

{
  "mcpServers": {
    "ultra-mcp": {
      "command": "npx",
      "args": ["-y", "ultra-mcp@latest"]
    }
  }
}

Ultra MCP will automatically use the API keys you configured with the config command.

MCP Tools & Prompts

Ultra MCP provides powerful AI tools accessible through Claude Code and Cursor. New in v0.7.0: All tools are now also available as discoverable prompts in Claude Code.

🎯 Prompts Support (New in v0.7.0)

All Ultra MCP tools are now exposed as discoverable prompts in Claude Code, making them even easier to use:

  • 25 discoverable prompts corresponding to all existing tools
  • Parameter guidance built into each prompt template
  • Natural language interface for all AI capabilities
  • Automatic discovery by Claude Code and other MCP clients

How to use prompts:

  1. Type / in Claude Code to see available prompts
  2. Select any Ultra MCP prompt (e.g., "Deep Reasoning", "Code Review", "Debug Issue")
  3. Fill in the parameters through the guided interface
  4. Claude automatically generates the appropriate instruction

This makes Ultra MCP's powerful AI capabilities more accessible than ever!

🧠 Deep Reasoning (deep-reasoning)

Leverage advanced AI models for complex problem-solving and analysis.

  • Default: GPT-5 for OpenAI/Azure, Gemini 2.5 Pro with Google Search, Grok-4 for xAI
  • Use Cases: Complex algorithms, architectural decisions, deep analysis

🔍 Investigate (investigate)

Thoroughly investigate topics with configurable depth levels.

  • Depth Levels: shallow, medium, deep
  • Google Search: Enabled by default for Gemini
  • Use Cases: Research topics, explore concepts, gather insights

📚 Research (research)

Conduct comprehensive research with multiple output formats.

  • Output Formats: summary, detailed, academic
  • Use Cases: Literature reviews, technology comparisons, documentation

📋 List Models (list-ai-models)

View all available AI models and their configuration status.

Example Usage

// In Claude Code or Cursor with MCP
await use_mcp_tool('ultra-mcp', 'deep-reasoning', {
  provider: 'openai',
  prompt: 'Design a distributed caching system for microservices',
  reasoningEffort: 'high',
});

Development

# Clone the repository
git clone https://github.com/RealMikeChong/ultra-mcp
cd ultra-mcp

# Install dependencies
bun install

# Build TypeScript
bun run build

# Run tests
bun run test

# Development mode with watch
bun run dev

# Test with MCP Inspector
npx @modelcontextprotocol/inspector node dist/cli.js

Architecture

Ultra MCP acts as a bridge between multiple AI model providers and MCP clients:

  1. MCP Protocol Layer: Implements Model Context Protocol for Claude Code/Cursor communication
  2. Model Providers: Integrates OpenAI, Google (Gemini), Azure OpenAI, and xAI Grok via Vercel AI SDK
  3. Unified Interface: Single MCP interface to access multiple AI models
  4. Configuration Management: Secure local storage with schema validation

Key Components

  • src/cli.ts - CLI entry point with commander
  • src/server.ts - MCP server implementation
  • src/config/ - Configuration management with schema validation
  • src/handlers/ - MCP protocol handlers
  • src/providers/ - Model provider implementations
  • src/utils/ - Shared utilities for streaming and error handling

Configuration Storage

Ultra MCP stores configuration in your system's default config directory:

  • macOS: ~/Library/Preferences/ultra-mcp-nodejs/
  • Linux: ~/.config/ultra-mcp/
  • Windows: %APPDATA%\ultra-mcp-nodejs\

Environment Variables

You can also set API keys and base URLs via environment variables:

  • OPENAI_API_KEY

FAQ

What is the Ultra (Multi-AI Provider) MCP server?
Ultra (Multi-AI Provider) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Ultra (Multi-AI Provider)?
This profile displays 51 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.651 reviews
  • Ira Martinez· Dec 24, 2024

    We wired Ultra (Multi-AI Provider) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Amina Desai· Dec 20, 2024

    Useful MCP listing: Ultra (Multi-AI Provider) is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Ganesh Mohane· Dec 16, 2024

    We wired Ultra (Multi-AI Provider) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Shikha Mishra· Dec 12, 2024

    I recommend Ultra (Multi-AI Provider) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Xiao Flores· Dec 4, 2024

    Ultra (Multi-AI Provider) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Amina Sharma· Dec 4, 2024

    I recommend Ultra (Multi-AI Provider) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Kofi Bansal· Nov 23, 2024

    Ultra (Multi-AI Provider) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Amina Martin· Nov 23, 2024

    Strong directory entry: Ultra (Multi-AI Provider) surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Kofi Desai· Nov 11, 2024

    Ultra (Multi-AI Provider) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Yash Thakker· Nov 3, 2024

    Strong directory entry: Ultra (Multi-AI Provider) surfaces stars and publisher context so we could sanity-check maintenance before adopting.

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