What can you do with this server?

This server provides access to multiple Large Language Model (LLM) APIs including ChatGPT, Claude, and DeepSeek through a Model Context Protocol (MCP) interface, along with Bitcoin and Lightning network operations. LLM Capabilities: * Call individual LLMs: Use tools like call-chatgpt, call-claude, and call-deepseek to send prompts to specific AI providers with configurable parameters like model, temperature, and token limits * Combine LLM responses: Use call-all-llms to send the same prompt to all available LLMs simultaneously and receive combined output with individual responses and a summary * Dynamic provider selection: Use call-llm to select an LLM provider ("chatgpt", "claude", or "deepseek") at runtime * Compare model outputs: Facilitate multi-perspective analysis, model comparison, and quality assurance Bitcoin & Lightning Network Features: * Generate new Bitcoin key pairs and addresses * Validate Bitcoin addresses * Decode raw Bitcoin transactions from hexadecimal * Retrieve latest Bitcoin block information * Get specific Bitcoin transaction details using transaction ID * Decode BOLT11 Lightning invoices * Pay BOLT11 Lightning invoices Configuration: Set environment variables for API keys (OPENAI_API_KEY, ANTHROPIC_API_KEY, DEEPSEEK_API_KEY) and default models for each provider.

Which integrations are available for this server?

Used for managing environment variables including API keys and default model configurations for the various LLM providers. Provides access to OpenAI's ChatGPT API for generating responses from various GPT models with customizable parameters for temperature and token limits. Implements schema validation for tool parameters to ensure proper formatting of requests to the different LLM APIs.

How do I use Cross-LLM MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Cross-LLM MCP Server call ChatGPT to explain quantum computing in simple terms" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

🤖 Cross-LLM MCP Server

Access multiple LLM APIs from one place. Call ChatGPT, Claude, DeepSeek, Gemini, Grok, Kimi, Perplexity, and Mistral with intelligent model selection, preferences, and prompt logging.

An MCP (Model Context Protocol) server that provides unified access to multiple Large Language Model APIs for AI coding environments like Cursor and Claude Desktop.

Trust Score

Why Use Cross-LLM MCP?

🌐 8 LLM Providers – ChatGPT, Claude, DeepSeek, Gemini, Grok, Kimi, Perplexity, Mistral
🎯 Smart Model Selection – Tag-based preferences (coding, business, reasoning, math, creative, general)
📊 Prompt Logging – Track all prompts with history, statistics, and analytics
💰 Cost Optimization – Choose flagship or cheaper models based on preference
⚡ Easy Setup – One-click install in Cursor or simple manual setup
🔄 Call All LLMs – Get responses from all providers simultaneously

Related MCP server: URL Fetch MCP

Quick Start

Ready to access multiple LLMs? Install in seconds:

Install in Cursor (Recommended):

🔗 Install in Cursor

Or install manually:

npm install -g cross-llm-mcp # Or from source: git clone https://github.com/JamesANZ/cross-llm-mcp.git cd cross-llm-mcp && npm install && npm run build

Features

🤖 Individual LLM Tools

call-chatgpt – OpenAI's ChatGPT API
call-claude – Anthropic's Claude API
call-deepseek – DeepSeek API
call-gemini – Google's Gemini API
call-grok – xAI's Grok API
call-kimi – Moonshot AI's Kimi API
call-perplexity – Perplexity AI API
call-mistral – Mistral AI API

🔄 Combined Tools

call-all-llms – Call all LLMs with the same prompt
call-llm – Call a specific provider by name

⚙️ Preferences & Model Selection

get-user-preferences – Get current preferences
set-user-preferences – Set default model, cost preference, and tag-based preferences
get-models-by-tag – Find models by tag (coding, business, reasoning, math, creative, general)

📝 Prompt Logging

get-prompt-history – View prompt history with filters
get-prompt-stats – Get statistics about prompt logs
delete-prompt-entries – Delete log entries by criteria
clear-prompt-history – Clear all prompt logs

Installation

Cursor (One-Click)

Click the install link above or use:

cursor://anysphere.cursor-deeplink/mcp/install?name=cross-llm-mcp&config=eyJjcm9zcy1sbG0tbWNwIjp7ImNvbW1hbmQiOiJucHgiLCJhcmdzIjpbIi15IiwiY3Jvc3MtbGxtLW1jcCJdfX0=

After installation, add your API keys in Cursor settings (see Configuration below).

Manual Installation

Requirements: Node.js 18+ and npm

# Clone and build git clone https://github.com/JamesANZ/cross-llm-mcp.git cd cross-llm-mcp npm install npm run build

Claude Desktop

Add to claude_desktop_config.json:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{ "mcpServers": { "cross-llm-mcp": { "command": "node", "args": ["/absolute/path/to/cross-llm-mcp/build/index.js"], "env": { "OPENAI_API_KEY": "your_openai_api_key_here", "ANTHROPIC_API_KEY": "your_anthropic_api_key_here", "DEEPSEEK_API_KEY": "your_deepseek_api_key_here", "GEMINI_API_KEY": "your_gemini_api_key_here", "XAI_API_KEY": "your_grok_api_key_here", "KIMI_API_KEY": "your_kimi_api_key_here", "PERPLEXITY_API_KEY": "your_perplexity_api_key_here", "MISTRAL_API_KEY": "your_mistral_api_key_here" } } } }

Restart Claude Desktop after configuration.

Configuration

API Keys

Set environment variables for the LLM providers you want to use:

export OPENAI_API_KEY="your_openai_api_key" export ANTHROPIC_API_KEY="your_anthropic_api_key" export DEEPSEEK_API_KEY="your_deepseek_api_key" export GEMINI_API_KEY="your_gemini_api_key" export XAI_API_KEY="your_grok_api_key" export KIMI_API_KEY="your_kimi_api_key" export PERPLEXITY_API_KEY="your_perplexity_api_key" export MISTRAL_API_KEY="your_mistral_api_key"

Getting API Keys

OpenAI: https://platform.openai.com/api-keys
Anthropic: https://console.anthropic.com/
DeepSeek: https://platform.deepseek.com/
Google Gemini: https://makersuite.google.com/app/apikey
xAI Grok: https://console.x.ai/
Moonshot AI: https://platform.moonshot.ai/
Perplexity: https://www.perplexity.ai/hub
Mistral: https://console.mistral.ai/

Usage Examples

Call ChatGPT

Get a response from OpenAI:

{ "tool": "call-chatgpt", "arguments": { "prompt": "Explain quantum computing in simple terms", "temperature": 0.7, "max_tokens": 500 } }

Call All LLMs

Get responses from all providers:

{ "tool": "call-all-llms", "arguments": { "prompt": "Write a short poem about AI", "temperature": 0.8 } }

Set Tag-Based Preferences

Automatically use the best model for each task type:

{ "tool": "set-user-preferences", "arguments": { "defaultModel": "gpt-4o", "costPreference": "cheaper", "tagPreferences": { "coding": "deepseek-r1", "general": "gpt-4o", "business": "claude-3.5-sonnet-20241022", "reasoning": "deepseek-r1", "math": "deepseek-r1", "creative": "gpt-4o" } } }

Get Prompt History

View your prompt logs:

{ "tool": "get-prompt-history", "arguments": { "provider": "chatgpt", "limit": 10 } }

Model Tags

Models are tagged by their strengths:

coding: deepseek-r1, deepseek-coder, gpt-4o, claude-3.5-sonnet-20241022
business: claude-3-opus-20240229, gpt-4o, gemini-1.5-pro
reasoning: deepseek-r1, o1-preview, claude-3.5-sonnet-20241022
math: deepseek-r1, o1-preview, o1-mini
creative: gpt-4o, claude-3-opus-20240229, gemini-1.5-pro
general: gpt-4o-mini, claude-3-haiku-20240307, gemini-1.5-flash

Use Cases

Multi-Perspective Analysis – Get different perspectives from multiple LLMs
Model Comparison – Compare responses to understand strengths and weaknesses
Cost Optimization – Choose the most cost-effective model for each task
Quality Assurance – Cross-reference responses from multiple models
Intelligent Selection – Automatically use the best model for coding, business, reasoning, etc.
Prompt Analytics – Track usage, costs, and patterns with automatic logging

Technical Details

Built with: Node.js, TypeScript, MCP SDK
Dependencies: @modelcontextprotocol/sdk, superagent, zod
Platforms: macOS, Windows, Linux

Preference Storage:

Unix/macOS: ~/.cross-llm-mcp/preferences.json
Windows: %APPDATA%/cross-llm-mcp/preferences.json

Prompt Log Storage:

Unix/macOS: ~/.cross-llm-mcp/prompts.json
Windows: %APPDATA%/cross-llm-mcp/prompts.json

Contributing

⭐ If this project helps you, please star it on GitHub! ⭐

Contributions welcome! Please open an issue or submit a pull request.

License

MIT License – see LICENSE.md for details.

Support

If you find this project useful, consider supporting it:

⚡ Lightning Network

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