cross-llm-mcp

- 🌐9 LLM Providers– ChatGPT, Claude, DeepSeek, Gemini, Grok, Kimi, Perplexity, Mistral, Hugging Face
- 🎯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

Ready to access multiple LLMs? Install in seconds:

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

- 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
- call-huggingface– Hugging Face Inference Router (OpenAI-compatible Hub models)

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

- 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)

- 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

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

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

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

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

Running Hub models locally (outside this MCP)

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

Get a response from a Hub model via the Inference Router (modelis the Hub repo id, e.g.Qwen/Qwen2.5-7B-Instruct):

{ "tool": "call-huggingface", "arguments": { "prompt": "Reply with exactly: ok", "model": "Qwen/Qwen2.5-7B-Instruct", "temperature": 0.3, "max_tokens": 32 } }

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

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" } } }

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

- 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

- 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

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

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

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

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

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

If you find this project useful, consider supporting it:

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