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Dialogflow API MCP Server

MCP Server generated by mcp.ag2.ai

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "ag2-mcp-servers-dialogflow-api": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "A JSON string containing the configuration.",
        "SECURITY": "Environment variables for security parameters (e.g., API keys)",
        "CONFIG_PATH": "Path to a JSON configuration file (e.g., mcp_server/mcp_config.json)"
      }
    }
  }
}

You run an MCP (Model Context Protocol) server that exposes your API as an MCP endpoint, enabling clients to interact with Dialogflow v3beta1 through a consistent, protocol-driven interface. This server automates the MCP connections and allows you to test, integrate, and route model-context actions with ease.

How to use

Start the MCP server in stdio mode to communicate via standard input and output with your MCP client. After the server is running, configure your client to connect through the process’s standard I/O streams and send the appropriate MCP requests defined by your client’s integration flow. You can use the provided environment variables to tailor security and configuration behavior (see environment variables below). If you need to stop the server, terminate the process gracefully.

How to install

Prerequisites: Python 3.9+ and a working Python toolchain (pip and uv). Ensure these are installed on your system before proceeding.

Step 1: Clone the repository.

git clone <repository-url>
cd mcp_server

Step 2: Install dependencies. If you are using a development container, dependencies are installed via the development setup script. Otherwise, run the following to install in editable mode.

pip install -e ".[dev]"
```
Alternatively, you can use the UV runtime to install editable dev dependencies.

uv pip install --editable ".[dev]"

Step 3: Start the server in stdio mode. This runs the MCP server so it can communicate through standard input and output with your client.

python mcp_server/main.py stdio

Additional sections

Configuration options are provided via environment variables. You can customize how the server runs by supplying values for these variables.

Environment variables to know about include:

- CONFIG_PATH: Path to a JSON configuration file (for example, mcp_server/mcp_config.json).

- CONFIG: A JSON string containing the configuration.

- SECURITY: Environment variables that define security parameters (for example, API keys).

Available tools

ruff

Lints and formats the codebase to enforce style and catch issues.

mypy

Performs static type checking to catch type errors before runtime.

pytest

Runs the test suite to verify functionality and catch regressions.

pre-commit

Runs a set of checks before each commit to maintain code quality.

hatch

Builds and publishes the project.