pr-mcp-server

review

Analyzes git diff and project context to generate a structured prompt for AI to produce a code review with summary, critical issues, suggestions, and decision.

Instructions

⚠️ CRITICAL: This tool ONLY returns an ANALYSIS PROMPT for YOU (Claude), NOT a final review. OUTPUT: You receive comprehensive context (project type, diff, commits, structure) formatted as a detailed prompt with instructions. YOUR JOB: Analyze that context and generate the actual code review following the exact format specified in the prompt. The prompt includes everything you need: project context, full diff, testing framework, architecture details. YOU must read it, analyze the code changes, and write a concise review (max 10-15 lines) with sections: Summary, Critical Issues, Key Suggestions, Decision (APPROVE/REQUEST_CHANGES). DO NOT return the prompt itself - generate YOUR review. Works for ANY language/framework because context is provided. Use when user asks to review code or when creating PR with review.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "review"
  }
}

Input Schema

Name	Required	Description	Default
`baseBranch`	No	Base branch for comparison (auto-detected if not provided)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 6, 2026

TDQS

A4.3/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description is highly transparent, warning with ⚠️ that the tool only returns a prompt, not a final review. It explains the exact output, the AI's job, and the review format. No annotations exist, so the description fully covers behavioral aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is fairly long but necessary given the tool's unusual workflow. It front-loads the critical warning and structures the explanation clearly. Slight redundancy could be trimmed, but overall it earns its length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description fully explains the tool's purpose, output, and the agent's role, including the expected review format. Despite the lack of an output schema, the description provides complete contextual information for proper usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single parameter 'baseBranch'. The description adds value by mentioning it is auto-detected if not provided, which goes beyond the schema's description. This extra context justifies a score above baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool returns an analysis prompt for the AI to generate a code review. It mentions using it when the user asks to review code, but does not explicitly differentiate from sibling tools like analyze_branch or create_pr.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use when user asks to review code or when creating PR with review.' It provides clear context for when to use, though it does not mention when not to use or compare to alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server