AVA MCP Server

# Model Context Protocol (MCP) All credits to : https://github.com/ShawhinT/YouTube-Blog/ Fourth example in AI agents series. Here, I build a customer MCP server to give any AI app access to a toolset for an Artificial Virtual Assistant (AVA). **Links** - [Video](https://youtu.be/N3vHJcHBS-w) - [Blog](https://medium.com/data-science-collective/model-context-protocol-mcp-explained-ef5c33c5fe05) ## How to run this example 1. Clone this repo 2. [Install uv](https://docs.astral.sh/uv/getting-started/installation/) if you haven't already ``` # Mac/Linux curl -LsSf https://astral.sh/uv/install.sh | sh # Windows powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" ``` 3. Test the server in dev mode ``` uv run mcp dev mcp-server-example.py ``` 4. Add server config to AI app (e.g. Claude Desktop or Cursor). ``` { "mcpServers": { "AVA": { "command": "/Users/shawhin/.local/bin/uv", # replace with global path to your uv installation "args": [ "--directory", "/Users/shawhin/Documents/_code/_stv/sandbox/ava-mcp/", # replace with global path to repo "run", "mcp-server-example.py" ] } } } ``` ## Customizing AVA's Behavior ### Update Personal Details and Preferences 1. Locate the `prompts/ava.md` file in your project directory 2. Customize the file with: - Communication preferences - Specific instructions for handling tasks - Any other relevant guidelines for AVA ## Environment Setup (.env) 1. Create a `.env` file in the root directory of the project with the following variables: ```env USER_EMAIL=your_email_address # Google OAuth Credentials GOOGLE_CREDENTIALS_PATH=.config/ava-agent/credentials.json GOOGLE_TOKEN_PATH=.config/ava-agent/token.json ``` ### Required Environment Variables: - `USER_EMAIL`: The Gmail address you want to use for this application - `GOOGLE_CREDENTIALS_PATH`: Path to your Google OAuth credentials file - `GOOGLE_TOKEN_PATH`: Path where the Google OAuth token will be stored ## Google OAuth Setup ### 1. Create Project Directory Structure First, create the required directory structure: ```bash mkdir -p .config/ava-agent ``` ### 2. Set Up Google Cloud Project 1. Go to the [Google Cloud Console](https://console.cloud.google.com/) 2. Create a new project or select an existing one 3. Enable the Gmail API: - In the navigation menu, go to "APIs & Services" > "Library" - Search for "Gmail API" - Click "Enable" ### 3. Create OAuth Credentials 1. In the Google Cloud Console: - Go to "APIs & Services" > "Credentials" - Click "Create Credentials" > "OAuth client ID" - Choose "Desktop application" as the application type - Give it a name (e.g., "AVA Gmail Client") - Click "Create" 2. Download the credentials: - After creation, click "Download JSON" - Save the downloaded file as `credentials.json` in `.config/ava-agent/` - The file should contain your client ID and client secret ### 4. Configure OAuth Consent Screen 1. In the Google Cloud Console: - Go to "APIs & Services" > "OAuth consent screen" - Choose "External" user type - Fill in the required information: - App name - User support email - Developer contact information - Add the Gmail API scope: `https://www.googleapis.com/auth/gmail.modify` - Add your email as a test user - Complete the configuration ## Signing into Google Before the server can access you Gmail account you will need to authorize it. You can do this by running `uv run oauth.py` which does the following. 1. Check for the presence of `token.json` 2. If not found, it will initiate the Google OAuth authentication flow 3. Guide you through the authentication process in your browser: - You'll be asked to sign in to your Google account - Grant the requested permissions - The application will automatically save the token 4. Generate and store the token automatically ## Security Notes ### File Protection - Never commit your `.env` file or `token.json` to version control - Keep your Google credentials secure - Add the following to your `.gitignore`: ``` .env .config/ava-agent/token.json .config/ava-agent/credentials.json ```