AI Peer Review 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 (required). Get it from Google AI Studio at https://ai.google.dev |
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| ai_peer_reviewB | Get peer review feedback from Google Gemini on your response to help improve accuracy and completeness |
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 1 tool
With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined and distinct by default.
A single tool inherently follows a consistent naming pattern. The tool name 'ai_peer_review' uses snake_case and clearly describes its function without any conflicting conventions.
A single tool is too few for a server named 'AI Peer Review MCP Server', which suggests a broader scope for peer review functionality. This minimal toolset limits the server's utility and feels incomplete for its apparent purpose.
The server is severely incomplete for peer review operations. It only provides feedback generation via one tool, lacking essential functions like managing reviews, listing past reviews, or handling different review types, which are expected in a peer review domain.