What are the prerequisites?
You need the Rust toolchain, a Gemini API key from Google AI Studio, and a supported shell (Bash or Zsh recommended for the `gemini` wrapper).
@frostdev-ops
Basic information
> Gemini Rust Suite 🦀: A powerful, modular Rust toolkit for interacting with Google Gemini. Features a feature-rich CLI, persistent semantic memory (LanceDB), and extensible tool integration via the Model Context Protocol (MCP).
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Gemini Rust Suite is a collection of Rust crates for interacting with Google Gemini models. It enables tool usage via the Model Context Protocol (MCP), persistent semantic memory using a vector database, and a command-line interface for Linux terminals.
Install by running the install.sh script from the repository root, which builds the binaries and configures a gemini shell wrapper. Configure your API key and settings in ~/.config/gemini-suite/config.toml. Use the gemini command for single prompts, interactive chat (-i), task loops (-t), or tool‑augmented queries.
You need the Rust toolchain, a Gemini API key from Google AI Studio, and a supported shell (Bash or Zsh recommended for the `gemini` wrapper).
The API key is read from `~/.config/gemini-suite/config.toml`, then from the `GEMINI_API_KEY` environment variable, and finally from a `.env` file in the current working directory.
The `gemini` wrapper function (added to your shell config) captures a session ID from the binary’s output and exports it. This allows subsequent commands to continue the same conversation. Without the wrapper, history persists only within a single interactive (`-i`) session.
The suite includes built‑in servers for filesystem operations (`filesystem`), command execution (`command`), and memory storage/embedding (`memory_store`).
Zsh users can use the `mcpd` helper function (installed by `install.sh`) with commands like `mcpd start`, `mcpd stop`, `mcpd status`, and `mcpd logs`.
XDC AI is a remote MCP server available at https://xdcai.tech.

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