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Gemini Example

jrmlhermittebyjrmlhermitte
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API Development
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Provides a foundational example for integrating custom tools with the Gemini CLI using the Model Context Protocol (MCP).

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Serves as a practical demonstration for developers looking to integrate custom functionality with the Gemini conversational AI environment. This example project showcases the fundamental steps of building a Model Context Protocol (MCP) server in Python, exposing a simple 'greet' tool. It further guides users through configuring the Gemini CLI to seamlessly discover and invoke this custom tool, illustrating how to extend Gemini's capabilities with external services and functions.

Key Features

01Demonstrates basic Model Context Protocol (MCP) server implementation.
02Utilizes the `fastmcp` Python library for quick setup.
03Illustrates `stdio` communication for MCP server interaction.
04Provides clear steps for integrating custom tools with Gemini CLI.
05Showcases defining and invoking custom tools within the Gemini environment.
060 GitHub stars

Use Cases

01Integrating external functionalities and APIs with the Gemini CLI.
02Learning the foundational concepts of the Model Context Protocol (MCP).
03Developing custom tools and services callable by AI models via MCP.