Code Review MCP Server

suggest_improvements

Analyze code and return actionable recommendations to improve performance, readability, and best practices, with an optional focus area.

Instructions

Suggest code quality improvements

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "code": "<code>"
    },
    "name": "suggest_improvements"
  }
}

Input Schema

Name	Required	Description	Default
`code`	Yes	The code to analyze
`focus`	No	Focus area (performance, readability, best_practices)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.1Oct 17, 2026

TDQS

C2.5/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It does not state whether the tool is read-only, whether it modifies or returns code, whether it needs repository access, or what form the suggestions take, leaving the agent with essentially no behavioral signal.

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

Conciseness3/5

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

It is a single short sentence with no redundancy, which is superficially efficient. But it is under-specified rather than genuinely concise, and the brevity comes at the cost of any actionable detail.

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

Completeness2/5

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

With two parameters, no output schema, and no annotations, the description needed to explain return behavior and usage context, and it does neither. An agent knows only the rough function and nothing about what it will get back or when to pick this over its siblings.

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

Parameters3/5

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

Schema description coverage is 100%, including an enum for focus, so the schema already documents both parameters fully. The description adds no additional meaning about the focus values or the expected code input, which meets the baseline-3 expectation when the schema does the heavy lifting.

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

Purpose3/5

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

The description names a specific verb (suggest) and resource (code quality improvements), so the basic purpose is legible. However, it is nearly indistinguishable from the sibling review_code and does nothing to separate itself from analyze_security, so an agent cannot confidently route between them from the text alone.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no when-not-to-use, and no mention of the sibling tools review_code or analyze_security. The agent is left to infer entirely when improvement suggestions are preferable to a code review or a security analysis.

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

Deploy Server