Gemini MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_API_KEY | Yes | Your Google Gemini API key |
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 |
|---|---|
| generateWithGeminiC | Generate content with Gemini 2.5 Pro Experimental (beta API) |
| getModelInfoB | Get information about the Gemini model being used |
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 2 tools
The two tools have completely distinct purposes: generateWithGemini is for content generation, while getModelInfo is for retrieving model metadata. There is no overlap in functionality, making it impossible to confuse them.
Both tools use camelCase naming, which is consistent. However, generateWithGemini uses a verb+preposition+noun pattern, while getModelInfo uses verb+noun, creating a minor deviation in structure.
With only 2 tools, the server feels thin for a Gemini API server, as it lacks operations like listing models, managing conversations, or handling multimodal inputs. The count is borderline for the apparent scope of interacting with a generative AI model.
The tool surface is severely incomplete for a Gemini API server. It only covers content generation and model info, missing essential operations such as chat/completion management, file uploads for multimodal inputs, or configuration settings, which will likely cause agent failures in complex workflows.