Claude Code Gemini MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_MODEL | No | Model ID | gemini-3-pro-preview |
| GEMINI_API_KEY | Yes | Your API key | |
| GEMINI_BASE_URL | Yes | API endpoint (OpenAI-compatible) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| gemini_thinkC | Let Gemini-3-pro-preview deeply analyze complex problems, perform reasoning and brainstorming |
| gemini_brainstormC | Let Gemini brainstorm on a topic and generate multiple creative ideas or solutions with pros and cons |
| gemini_reviewC | Let Gemini review code, architecture design, or technical solutions |
| gemini_queryC | Send any query to Gemini-3-pro-preview model |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Multiple tools have overlapping purposes that could cause confusion. gemini_brainstorm and gemini_think both involve generating ideas and analysis, while gemini_query is a general-purpose tool that could potentially cover the same ground. The descriptions don't clearly differentiate when to use each tool versus the others.
All tools follow a perfect gemini_verb pattern consistently throughout. The naming is completely predictable and follows the same structure for every tool, making it easy to understand the pattern.
With only 4 tools, the server feels somewhat thin for a general-purpose AI assistant interface. While the count isn't extreme, it's borderline minimal for what appears to be a Gemini API wrapper that could benefit from more specialized operations.
There are significant gaps in the tool surface for a Gemini API wrapper. Missing are basic operations like summarization, translation, content generation, or structured output formatting. The tools focus narrowly on brainstorming/thinking/review while omitting many common LLM use cases that agents would expect.