Repo with example code for building various types of agents using ADK
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install required Python packages/modules for the example you want to run:
pip install -r requirements.txt -
.envfile in your agent's folder (Google AI Studio)
GOOGLE_GENAI_USE_VERTEXAI=FALSE
GOOGLE_API_KEY=a1b2c3yourapikeyherex7y8z9
.envfile in your agent's folder (Vertex AI)
GOOGLE_GENAI_USE_VERTEXAI=TRUE
GOOGLE_CLOUD_PROJECT=myproject-123
GOOGLE_CLOUD_LOCATION=us-central1
NOTE: while you can use any location you wish, not all locations supports every Gemini model
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A very basic agent that leverages Google Search as the tool to help the user find answers. If you're new to programming and/or ADK, I suggest you start here :)
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Simple Weather and Time agent that uses function tools to find latitude & longitude of a given city, country and its weather and time (timezone-adjusted). Uses sub-agents to handle specific tasks, each with its own persona. You can find a short write-up of it on my Medium. I wrote a follow-up article about Agent Evaluation and added the evalset and instructions to for this particular agent example. I then added a callback function to make the agent a little more robust.
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Model Context Protocol (MCP) example that uses FastMCP and ngrok to host the MCP server which the math agent connects to get tools to help it perform basic math (add/subtract/multiply/divide). Read about this on my Medium.
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Another MCP example. This time it is a travel recommendation agent that uses a local Google Maps Platform MCP server (via Stdio) to find attractions and restaurants near a give origin location. In its current form, the directions and travel distance returned can be quite wrong and hence I wouldn't really rely on it for directions. I built my own Google Maps MCP server (in Python) that I'll be using going forward in future examples.