Multi-Model Advisor (Ollama) MCP server

The Multi-Model Advisor is an MCP server that queries multiple Ollama models and combines their responses, providing diverse AI perspectives on a single question. It creates a "council of advisors" approach where Claude can synthesize multiple viewpoints to provide more comprehensive answers.

Prerequisites

• Node.js 16.x or higher
• Ollama installed and running (see Ollama installation)
• Claude for Desktop (for the complete advisory experience)

Installation Options

Installing via Smithery

To install multi-ai-advisor-mcp for Claude Desktop automatically:

npx -y @smithery/cli install @YuChenSSR/multi-ai-advisor-mcp --client claude

Manual Installation

1. Clone the repository:

   git clone https://github.com/YuChenSSR/multi-ai-advisor-mcp.git 
   cd multi-ai-advisor-mcp
   

2. Install dependencies:

   npm install
   

3. Build the project:

   npm run build
   

4. Install required Ollama models:

   ollama pull gemma3:1b
   ollama pull llama3.2:1b
   ollama pull deepseek-r1:1.5b
   

Configuration

Create a .env file in the project root with your desired configuration:

# Server configuration
SERVER_NAME=multi-model-advisor
SERVER_VERSION=1.0.0
DEBUG=true

# Ollama configuration
OLLAMA_API_URL=http://localhost:11434
DEFAULT_MODELS=gemma3:1b,llama3.2:1b,deepseek-r1:1.5b

# System prompts for each model
GEMMA_SYSTEM_PROMPT=You are a creative and innovative AI assistant. Think outside the box and offer novel perspectives.
LLAMA_SYSTEM_PROMPT=You are a supportive and empathetic AI assistant focused on human well-being. Provide considerate and balanced advice.
DEEPSEEK_SYSTEM_PROMPT=You are a logical and analytical AI assistant. Think step-by-step and explain your reasoning clearly.

Connect to Claude for Desktop

1. Locate your Claude for Desktop configuration file:

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

2. Edit the file to add the Multi-Model Advisor MCP server:

{
  "mcpServers": {
    "multi-model-advisor": {
      "command": "node",
      "args": ["/absolute/path/to/multi-ai-advisor-mcp/build/index.js"]
    }
  }
}

3. Replace /absolute/path/to/ with the actual path to your project directory

4. Restart Claude for Desktop

Usage

List Available Models

To see all available models on your system:

Show me which Ollama models are available on my system

This will display all installed Ollama models and indicate which ones are configured as defaults.

Basic Usage

Simply ask Claude to use the multi-model advisor:

what are the most important skills for success in today's job market, 
you can use gemma3:1b, llama3.2:1b, deepseek-r1:1.5b to help you 

Claude will query all default models and provide a synthesized response based on their different perspectives.

How It Works

1. The MCP server exposes two tools:

   • list-available-models: Shows all Ollama models on your system
   • query-models: Queries multiple models with a question

2. When you ask Claude a question referring to the multi-model advisor:

   • Claude decides to use the query-models tool
   • The server sends your question to multiple Ollama models
   • Each model responds with its perspective
   • Claude receives all responses and synthesizes a comprehensive answer

3. Each model can have a different "persona" or role assigned, encouraging diverse perspectives.

Troubleshooting

Ollama Connection Issues

If the server can't connect to Ollama:

• Ensure Ollama is running (ollama serve)
• Check that the OLLAMA_API_URL is correct in your .env file
• Try accessing http://localhost:11434 in your browser to verify Ollama is responding

Model Not Found

If a model is reported as unavailable:

• Check that you've pulled the model using ollama pull <model-name>
• Verify the exact model name using ollama list
• Use the list-available-models tool to see all available models

Claude Not Showing MCP Tools

If the tools don't appear in Claude:

• Ensure you've restarted Claude after updating the configuration
• Check the absolute path in claude_desktop_config.json is correct
• Look at Claude's logs for error messages

RAM is not enough

Some managers' AI models may have chosen larger models, but there is not enough memory to run them. You can try specifying a smaller model (see the Basic Usage section) or upgrading the memory.

How to add this MCP server to Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > MCP and click "Add new global MCP server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "cursor-rules-mcp": {
            "command": "npx",
            "args": [
                "-y",
                "cursor-rules-mcp"
            ]
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explictly ask the agent to use the tool by mentioning the tool name and describing what the function does.