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react-render-profile-mcp

react-render-profile-mcp

by vola-trebla
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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suggest_memoization

Analyze React profiling data to identify components with wasteful re-renders and get concrete React.memo suggestions.

Instructions

Analyzes the profiling data and returns concrete memoization suggestions. Currently detects React.memo candidates: components with spurious renders above the wasted ms threshold. Each suggestion explains why the component re-renders unnecessarily and what to do about it.

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": {
      "profile_path": "<profile_path>"
    },
    "name": "suggest_memoization"
  }
}

Input Schema

NameRequiredDescriptionDefault
profile_pathYesAbsolute path to the React DevTools Profiler export (.json)
min_wasted_msNoOnly suggest for components wasting more than this many ms total (default: 0)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A3.8/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden. It adequately discloses non-mutating analysis behavior, the current React.memo-only scope, and the content of returned suggestions (why and what to do). This sets proper expectations.

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

Conciseness5/5

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

Three sentences, front-loaded with the main purpose, and no filler. Each sentence adds value: what the tool does, the current detection scope, and what each suggestion contains.

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

Completeness4/5

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

For a two-parameter read-only analysis tool with no output schema, the description is adequately complete. It explains the input purpose, the threshold semantics, and the nature of the output. It doesn't describe exact return format, but the high-level explanation is sufficient for tool selection and invocation.

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%, so the schema already documents both parameters. The description adds a little extra context by linking 'wasted ms threshold' to min_wasted_ms, but it doesn't add meaning beyond what the schema provides.

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 uses a specific verb ('Analyzes...returns') and names the resource ('profiling data') and concrete output ('memoization suggestions', 'React.memo candidates'). It is clear and distinct from siblings like find_spurious_renders, though it doesn't explicitly name alternatives.

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

Usage Guidelines3/5

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

The description implies the tool is for use when you want memoization suggestions from profiling data, but it provides no explicit when-not-to-use guidance or alternatives. Context is clear enough, but it lacks exclusions.

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

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