Ollama MCP Database Assistant

by robdodson

33 stars
1 downloads
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GitHub

About

An interactive chat interface that combines Ollama's LLM capabilities with PostgreSQL database access through the Model Context Protocol (MCP). Ask questions about your data in natural language and get AI-powered responses backed by real SQL queries.

Details

Author
robdodson
Repository
robdodson/ollama-mcp-db
GitHub stars
33
Downloads
1
Categories
AI
Tags
#data

- Natural language interface to your PostgreSQL database
- Automatic SQL query generation
- Schema-aware responses
- Interactive chat interface
- Secure, read-only database access

Setting up with Highlight

Follow these steps to add this server as a custom Highlight plugin:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Ollama MCP Database Assistant
    Command (node, npx, python, etc.) npx
    Arguments
    • Argument 1 -y
    • Argument 2 @highlight/mcp-server

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

1. Start the chat interface:

npm start

2. Ask questions about your data in natural language:

Connected to database. You can now ask questions about your data.
Type "exit" to quit.

What would you like to know about your data? Which products generated the most revenue last month?
Analyzing...

[AI will generate and execute a SQL query, then explain the results]

3. Type 'exit' to quit the application.

| Variable | Description | Default |
| ------------ | ---------------------------- | ------------------------- |
| DATABASE_URL | PostgreSQL connection string | Required |
| OLLAMA_MODEL | Ollama model to use | qwen2.5-coder:7b-instruct |

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "ollama mcp database assistant": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Linux

{
    "env": [],
    "args": [
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "npx"
}

Macos

{
    "env": [],
    "args": [
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "npx"
}

Windows

{
    "env": [],
    "args": [
        "/c",
        "npx",
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "cmd"
}

Ollama MCP Database Assistant

An interactive chat interface that combines Ollama's LLM capabilities with PostgreSQL database access through the Model Context Protocol (MCP). Ask questions about your data in natural language and get AI-powered responses backed by real SQL queries.

Features

- Natural language interface to your PostgreSQL database
- Automatic SQL query generation
- Schema-aware responses
- Interactive chat interface
- Secure, read-only database access

Prerequisites

- Node.js 16 or higher
- A running PostgreSQL database
- Ollama installed and running locally
- The qwen2.5-coder:7b-instruct model pulled in Ollama

Setup

1. Clone the repository:

git clone [your-repo-url]
cd [your-repo-name]

2. Install dependencies:

npm install

3. Pull the required Ollama model:

ollama pull qwen2.5-coder:7b-instruct

4. Create a .env file in the project root:

DATABASE_URL=postgresql://user:password@localhost:5432/dbname
OLLAMA_MODEL=qwen2.5-coder:7b-instruct  # Optional - this is the default

Usage

1. Start the chat interface:

npm start

2. Ask questions about your data in natural language:

Connected to database. You can now ask questions about your data.
Type "exit" to quit.

What would you like to know about your data? Which products generated the most revenue last month?
Analyzing...

[AI will generate and execute a SQL query, then explain the results]

3. Type 'exit' to quit the application.

How It Works

1. The application connects to your PostgreSQL database through the PostgreSQL MCP server
2. It loads and caches your database schema
3. When you ask a question:
- The schema and question are sent to Ollama
- Ollama generates an appropriate SQL query
- The query is executed through MCP
- Results are sent back to Ollama for interpretation
- You receive a natural language response

Environment Variables

| Variable | Description | Default |
| ------------ | ---------------------------- | ------------------------- |
| DATABASE_URL | PostgreSQL connection string | Required |
| OLLAMA_MODEL | Ollama model to use | qwen2.5-coder:7b-instruct |

Security

- All database access is read-only
- SQL queries are restricted to SELECT statements
- Database credentials are kept secure in your .env file

Development

Built with:

- TypeScript
- Model Context Protocol (MCP)
- Ollama
- PostgreSQL

Troubleshooting

Common Issues

1. "Failed to connect to database"

- Check your DATABASE_URL in .env
- Verify PostgreSQL is running
- Check network connectivity

2. "Failed to connect to Ollama"

- Ensure Ollama is running (ollama serve)
- Verify the model is installed (ollama list)

3. "Error executing query"
- Check database permissions
- Verify table/column names in the schema

License

MIT

Contributing

1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Open a Pull Request

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