Building MCP Servers with Google Gemini
Building MCP Servers with Google Gemini
This repository contains the complete code for the tutorial on building Model Context Protocol (MCP) servers with Google's Gemini 2.0 model, as described in this blog post.
MCP is an open standard developed by Anthropic that enables AI models to seamlessly access external tools and resources. It creates a standardized way for AI models to interact with tools, access the internet, run code, and more, without needing custom integrations for each tool or model.
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| Variable | Description | Required |
|---|---|---|
| BRAVE_API_KEY | Credential the server authenticates with. | Yes |
| GOOGLE_API_KEY | Credential the server authenticates with. | Yes |
Read, search and edit files inside allowed directories with the Model Context Protocol reference Filesystem server.
Retrieve version-aware library documentation and code examples with Context7 MCP, using resolve-library-id and query-docs.
This is a Model Context Protocol (MCP) server that provides a tool for generating placeholder images from different providers.
ContextKeeper revolutionizes AI-assisted development by solving the fundamental problem of context loss between sessions. Using an LSM-tree inspired
Manage GitHub Actions workflows from your AI assistant. List runs, read logs, re-run failed jobs, cancel builds, and trigger deployments without leaving your editor.
Spanish invoice PDFs to validated data: NIF/IVA/IRPF extraction, arithmetic checks, IVA per quarter.