Ollama mcp

Local 2025-09-01 00:00:07 0

A bridge that enables seamless integration of Ollama's local LLM capabilities into MCP-powered applications, allowing users to manage and run AI models locally with full API coverage.

? A powerful bridge between Ollama and the Model Context Protocol (MCP), enabling seamless integration of Ollama's local LLM capabilities into your MCP-powered applications.

? Features

Complete Ollama Integration

Full API Coverage: Access all essential Ollama functionality through a clean MCP interface
OpenAI-Compatible Chat: Drop-in replacement for OpenAI's chat completion API
Local LLM Power: Run AI models locally with full control and privacy

Core Capabilities

? Model Management
Pull models from registries
Push models to registries
List available models
Create custom models from Modelfiles
Copy and remove models
? Model Execution
Run models with customizable prompts
Chat completion API with system/user/assistant roles
Configurable parameters (temperature, timeout)
Raw mode support for direct responses
? Server Control
Start and manage Ollama server
View detailed model information
Error handling and timeout management

? Getting Started

Prerequisites

Ollama installed on your system
Node.js and npm/pnpm

Installation

Install dependencies:
```
pnpm install
```
Build the server:
```
pnpm run build
```

Configuration

Add the server to your MCP configuration:

For Claude Desktop:

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

{
  "mcpServers": {
    "ollama": {
      "command": "node",
      "args": ["/path/to/ollama-server/build/index.js"],
      "env": {
        "OLLAMA_HOST": "http://127.0.0.1:11434"  // Optional: customize Ollama API endpoint
      }
    }
  }
}

? Usage Examples

Pull and Run a Model

// Pull a model
await mcp.use_mcp_tool({
  server_name: "ollama",
  tool_name: "pull",
  arguments: {
    name: "llama2"
  }
});

// Run the model
await mcp.use_mcp_tool({
  server_name: "ollama",
  tool_name: "run",
  arguments: {
    name: "llama2",
    prompt: "Explain quantum computing in simple terms"
  }
});

Chat Completion (OpenAI-compatible)

await mcp.use_mcp_tool({
  server_name: "ollama",
  tool_name: "chat_completion",
  arguments: {
    model: "llama2",
    messages: [
      {
        role: "system",
        content: "You are a helpful assistant."
      },
      {
        role: "user",
        content: "What is the meaning of life?"
      }
    ],
    temperature: 0.7
  }
});

Create Custom Model

await mcp.use_mcp_tool({
  server_name: "ollama",
  tool_name: "create",
  arguments: {
    name: "custom-model",
    modelfile: "./path/to/Modelfile"
  }
});

? Advanced Configuration

OLLAMA_HOST: Configure custom Ollama API endpoint (default: http://127.0.0.1:11434)
Timeout settings for model execution (default: 60 seconds)
Temperature control for response randomness (0-2 range)

? Contributing

Contributions are welcome! Feel free to: - Report bugs - Suggest new features - Submit pull requests

? License

MIT License - feel free to use in your own projects!

Built with ❤️ for the MCP ecosystem

[
  {
    "description": "Start Ollama server",
    "inputSchema": {
      "additionalProperties": false,
      "properties": {},
      "type": "object"
    },
    "name": "serve"
  },
  {
    "description": "Create a model from a Modelfile",
    "inputSchema": {
      "additionalProperties": false,
      "properties": {
        "modelfile": {
          "description": "Path to Modelfile",
          "type": "string"
        },
        "name": {
          "description": "Name for the model",
          "type": "string"
        }
      },
      "required": [
        "name",
        "modelfile"
      ],
      "type": "object"
    },
    "name": "create"
  },
  {
    "description": "Show information for a model",
    "inputSchema": {
      "additionalProperties": false,
      "properties": {
        "name": {
          "description": "Name of the model",
          "type": "string"
        }
      },
      "required": [
        "name"
      ],
      "type": "object"
    },
    "name": "show"
  },
  {
    "description": "Run a model",
    "inputSchema": {
      "additionalProperties": false,
      "properties": {
        "name": {
          "description": "Name of the model",
          "type": "string"
        },
        "prompt": {
          "description": "Prompt to send to the model",
          "type": "string"
        },
        "timeout": {
          "description": "Timeout in milliseconds (default: 60000)",
          "minimum": 1000,
          "type": "number"
        }
      },
      "required": [
        "name",
        "prompt"
      ],
      "type": "object"
    },
    "name": "run"
  },
  {
    "description": "Pull a model from a registry",
    "inputSchema": {
      "additionalProperties": false,
      "properties": {
        "name": {
          "description": "Name of the model to pull",
          "type": "string"
        }
      },
      "required": [
        "name"
      ],
      "type": "object"
    },
    "name": "pull"
  },
  {
    "description": "Push a model to a registry",
    "inputSchema": {
      "additionalProperties": false,
      "properties": {
        "name": {
          "description": "Name of the model to push",
          "type": "string"
        }
      },
      "required": [
        "name"
      ],
      "type": "object"
    },
    "name": "push"
  },
  {
    "description": "List models",
    "inputSchema": {
      "additionalProperties": false,
      "properties": {},
      "type": "object"
    },
    "name": "list"
  },
  {
    "description": "Copy a model",
    "inputSchema": {
      "additionalProperties": false,
      "properties": {
        "destination": {
          "description": "Destination model name",
          "type": "string"
        },
        "source": {
          "description": "Source model name",
          "type": "string"
        }
      },
      "required": [
        "source",
        "destination"
      ],
      "type": "object"
    },
    "name": "cp"
  },
  {
    "description": "Remove a model",
    "inputSchema": {
      "additionalProperties": false,
      "properties": {
        "name": {
          "description": "Name of the model to remove",
          "type": "string"
        }
      },
      "required": [
        "name"
      ],
      "type": "object"
    },
    "name": "rm"
  },
  {
    "description": "OpenAI-compatible chat completion API",
    "inputSchema": {
      "additionalProperties": false,
      "properties": {
        "messages": {
          "description": "Array of messages in the conversation",
          "items": {
            "properties": {
              "content": {
                "type": "string"
              },
              "role": {
                "enum": [
                  "system",
                  "user",
                  "assistant"
                ],
                "type": "string"
              }
            },
            "required": [
              "role",
              "content"
            ],
            "type": "object"
          },
          "type": "array"
        },
        "model": {
          "description": "Name of the Ollama model to use",
          "type": "string"
        },
        "temperature": {
          "description": "Sampling temperature (0-2)",
          "maximum": 2,
          "minimum": 0,
          "type": "number"
        },
        "timeout": {
          "description": "Timeout in milliseconds (default: 60000)",
          "minimum": 1000,
          "type": "number"
        }
      },
      "required": [
        "model",
        "messages"
      ],
      "type": "object"
    },
    "name": "chat_completion"
  }
]