by realmikechong
Ultra (Multi-AI Provider) unifies OpenAI, Gemini, and Azure models, tracking usage, estimating costs, and offering 9 dev
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.
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.
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.
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.
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
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
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
Share your MCP server with the developer community
We wired Ultra (Multi-AI Provider) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Useful MCP listing: Ultra (Multi-AI Provider) is the kind of server we cite when onboarding engineers to host + tool permissions.
We wired Ultra (Multi-AI Provider) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
I recommend Ultra (Multi-AI Provider) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Ultra (Multi-AI Provider) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
I recommend Ultra (Multi-AI Provider) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Ultra (Multi-AI Provider) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: Ultra (Multi-AI Provider) surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Ultra (Multi-AI Provider) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Strong directory entry: Ultra (Multi-AI Provider) surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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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.
This project is inspired by:
While inspired by zen-mcp-server, Ultra MCP offers several key advantages:
npx ultra-mcp to get startednpm install -g ultra-mcpnpx ultra-mcp confignpx ultra-mcp db:statsnpx ultra-mcp dashboardconf library# Install globally via npm
npm install -g ultra-mcp
# Or run directly with npx
npx -y ultra-mcp config
Set up your API keys interactively:
npx -y ultra-mcp config
This will:
New in v0.5.10:
# Run the MCP server
npx -y ultra-mcp
# Or after building locally
bun run build
node dist/cli.js
Ultra MCP provides several powerful commands:
config - Interactive Configurationnpx -y ultra-mcp config
Configure API keys interactively with a user-friendly menu system.
dashboard - Web Dashboardnpx -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 Codenpx -y ultra-mcp install
Automatically install Ultra MCP as an MCP server for Claude Code.
doctor - Health Checknpx -y ultra-mcp doctor
# Test connections to providers
npx -y ultra-mcp doctor --test
Check installation health and test API connections.
chat - Interactive Chatnpx -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.
db:show - Show Database Infonpx -y ultra-mcp db:show
Display database file location and basic statistics.
db:stats - Usage Statisticsnpx -y ultra-mcp db:stats
Show detailed usage statistics for the last 30 days including costs by provider.
db:view - Database Viewernpx -y ultra-mcp db:view
Launch Drizzle Studio to explore the usage database interactively.
# Install Ultra MCP for Claude Code
npx -y ultra-mcp install
This command will:
Add to your Claude Code settings:
{
"mcpServers": {
"ultra-mcp": {
"command": "npx",
"args": ["-y", "ultra-mcp@latest"]
}
}
}
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.
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.
All Ultra MCP tools are now exposed as discoverable prompts in Claude Code, making them even easier to use:
How to use prompts:
/ in Claude Code to see available promptsThis makes Ultra MCP's powerful AI capabilities more accessible than ever!
deep-reasoning)Leverage advanced AI models for complex problem-solving and analysis.
investigate)Thoroughly investigate topics with configurable depth levels.
research)Conduct comprehensive research with multiple output formats.
list-ai-models)View all available AI models and their configuration status.
// 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',
});
# 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
Ultra MCP acts as a bridge between multiple AI model providers and MCP clients:
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 handlingUltra MCP stores configuration in your system's default config directory:
~/Library/Preferences/ultra-mcp-nodejs/~/.config/ultra-mcp/%APPDATA%\ultra-mcp-nodejs\You can also set API keys and base URLs via environment variables:
OPENAI_API_KEYPrerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ 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.