Ollama MCP Server Demo

A beginner-friendly project that demonstrates how to build a simple Model Context Protocol (MCP) server using Python and connect it to a local Ollama model.

Overview

This project shows:

• How to interact with a local Ollama model using the REST API

• The difference between Ollama's Generate API and Chat API

• How to expose an Ollama model as an MCP tool

• How to configure and run an MCP server in VS Code

Related MCP server: mcp-ollama-code-analyzer

Project Structure

.
├── chat.py
├── generate.py
├── ollama_mcp_server.py
├── test_ollama.py
└── .vscode
    ├── mcp.json
    └── session.py

Architecture

MCP Client (VS Code)
        │
        ▼
Python MCP Server
        │
        ▼
Ollama API
        │
        ▼
gpt-oss:20b-cloud

Prerequisites

• Python 3.10+

• Ollama installed and running

• A downloaded Ollama model (e.g. gpt-oss:20b-cloud)

Installation

Clone the repository:

git clone <your-repository-url>
cd ollama-mcp-server-demo

Install dependencies:

pip install -r requirements.txt

Running Ollama

Start Ollama:

ollama serve

Verify available models:

ollama list

Testing Ollama

Run:

python test_ollama.py

If everything is working, the model will generate a response in the terminal.

Running the MCP Server

Start the MCP server:

python ollama_mcp_server.py

The server exposes the following MCP tool:

ask_ollama(prompt: str)

Example:

Prompt: Explain MCP

Response: Model Context Protocol (MCP) is...

Learning Objectives

This project helped me understand:

• MCP fundamentals

• MCP tools and servers

• Ollama APIs

• Local LLM integration

• VS Code MCP configuration

• Python-based AI tooling

Future Improvements

• Add multiple MCP tools

• Support chat history

• Add document search (RAG)

• Connect to SharePoint or Microsoft Graph

• Add logging and error handling

Author

Rohit Patil