Provides an interface to Google's Dialogflow API, enabling agents to create, manage, and interact with conversational agents and natural language understanding services through the Dialogflow v3beta1 API.
MCP Server
This project is an MCP (Multi-Agent Conversation Protocol) Server for the given OpenAPI URL - https://api.apis.guru/v2/specs/googleapis.com/dialogflow/v3beta1/openapi.json, auto-generated using AG2's MCP builder.
Prerequisites
- Python 3.9+
- pip and uv
Installation
- Clone the repository:
- Install dependencies:
The .devcontainer/setup.sh script handles installing dependencies using
pip install -e ".[dev]"
. If you are not using the dev container, you can run this command manually.Alternatively, you can useuv
:
Development
This project uses ruff
for linting and formatting, mypy
for static type checking, and pytest
for testing.
Linting and Formatting
To check for linting issues:
To format the code:
These commands are also available via the scripts/lint.sh script.
Static Analysis
To run static analysis (mypy, bandit, semgrep):
This script is also configured as a pre-commit hook in .pre-commit-config.yaml.
Running Tests
To run tests with coverage:
This will run pytest and generate a coverage report. For a combined report and cleanup, you can use:
Pre-commit Hooks
This project uses pre-commit hooks defined in .pre-commit-config.yaml. To install the hooks:
The hooks will run automatically before each commit.
Running the Server
The MCP server can be started using the mcp_server/main.py script. It supports different transport modes (e.g., stdio
, sse
, streamable-http
).
To start the server (e.g., in stdio mode):
The server can be configured using environment variables:
CONFIG_PATH
: Path to a JSON configuration file (e.g., mcp_server/mcp_config.json).CONFIG
: A JSON string containing the configuration.SECURITY
: Environment variables for security parameters (e.g., API keys).
Refer to the if __name__ == "__main__":
block in mcp_server/main.py for details on how these are loaded.
The tests/test_mcp_server.py file demonstrates how to start and interact with the server programmatically for testing.
Building and Publishing
This project uses Hatch for building and publishing. To build the project:
To publish the project:
These commands are also available via the scripts/publish.sh script.
This server cannot be installed
An MCP server that enables natural language interactions with Google's Dialogflow API, allowing users to create and manage conversational agents, intents, and entities through the Dialogflow v3beta1 API.
Related MCP Servers
- -securityFlicense-qualityAn MCP server that provides access to Google's API Discovery Service, allowing agents to discover and interact with Google APIs through natural language commands.Last updated -Python
- -securityFlicense-qualityAn MCP (Multi-Agent Conversation Protocol) Server providing natural language access to Google's Cloud Datastore services through the v1beta1 API.Last updated -Python
- -securityFlicense-qualityAn MCP (Multi-Agent Conversation Protocol) Server that enables interaction with Google Workflows API, allowing management of workflow executions and definitions through natural language commands.Last updated -Python
- -securityFlicense-qualityThis MCP Server provides a natural language interface to interact with Google's Policy Analyzer API, allowing users to analyze policies and evaluate compliance through conversations.Last updated -Python