Ultra (Multi-AI Provider)▌
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.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
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.
🚀 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.
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-mcpto 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
conflibrary - 🧪 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:
- Show current configuration status
- Present a provider-first menu to select which AI provider to configure
- Guide you through setting API keys, base URLs, and preferred models
- Store configuration securely on your system
- 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:
- Type
/in Claude Code to see available prompts - Select any Ultra MCP prompt (e.g., "Deep Reasoning", "Code Review", "Debug Issue")
- Fill in the parameters through the guided interface
- 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:
- MCP Protocol Layer: Implements Model Context Protocol for Claude Code/Cursor communication
- Model Providers: Integrates OpenAI, Google (Gemini), Azure OpenAI, and xAI Grok via Vercel AI SDK
- Unified Interface: Single MCP interface to access multiple AI models
- Configuration Management: Secure local storage with schema validation
Key Components
src/cli.ts- CLI entry point with commandersrc/server.ts- MCP server implementationsrc/config/- Configuration management with schema validationsrc/handlers/- MCP protocol handlerssrc/providers/- Model provider implementationssrc/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.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 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
4.6★★★★★51 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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