Gemini Code Review MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_MODEL | No | AI model selection (default: gemini-2.0-flash) | |
| GITHUB_TOKEN | No | GitHub token for PR reviews | |
| GEMINI_API_KEY | Yes | Your Gemini API key | |
| THINKING_BUDGET | No | Thinking tokens (default: auto) | |
| GEMINI_TEMPERATURE | No | Creativity (0.0-2.0, default: 0.5) |
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 | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_pr_reviewC | Generate code review for a GitHub Pull Request with configuration discovery. |
| generate_ai_code_reviewC | Generate AI-powered code review from context file, content, or project analysis. |
| ask_geminiC | Generates context from files and sends it to Gemini for a response. This tool combines context generation with a direct call to the Gemini API. |
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 3 tools
While ask_gemini is a general-purpose query tool, generate_ai_code_review and generate_pr_review are more specialized for code review, leading to potential overlap where an agent might choose the wrong tool for a review task. Descriptions help differentiate, but ambiguity remains.
All tool names use snake_case and follow a verb_noun pattern consistently. The only minor deviation is the use of 'ask' versus 'generate' as verbs, but overall the naming is predictable and clear.
With three tools, the server covers the core functionality of generating code reviews and querying Gemini, which is appropriate for a focused code review assistant. The count is slightly low but not unreasonable for its scope.
The tool set covers the main use cases: general query, AI code review from context, and PR-specific review. Minor gaps like review history or configuration management are absent but not critical for the server's stated purpose.