Gemini Pro MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_API_KEY | Yes | Your Gemini API key from Google AI Studio |
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 |
|---|---|
| generate_textC | Generate text using Gemini 2.5 Pro model |
| analyze_imageC | Analyze an image using Gemini 2.5 Pro Vision |
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: one analyzes images and the other generates text. There is no overlap in functionality, making it impossible to confuse them.
Both tools follow a consistent verb_noun pattern (analyze_image, generate_text) with clear, descriptive names that indicate their specific actions and targets.
With only two tools, the server feels under-scoped for a Gemini Pro MCP Server, which might be expected to offer more capabilities like editing, summarizing, or multimodal interactions beyond basic image analysis and text generation.
The toolset is severely incomplete for a Gemini Pro server, lacking essential operations such as editing text, summarizing content, handling multimodal inputs beyond images, or providing model configuration options, which limits agent workflows.