Skip to main content
Glama
souvikdu

perfonext-render-mcp

Get Rerender Causes

get_rerender_causes

Identify React components with repeated rerenders and get likely causes from a render profile, helping you fix performance issues in Next.js apps.

Instructions

Highlight components with repeated rerenders and explain likely causes using heuristics derived from the exported profile.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many components to include. Defaults to 10.
profileIdYesProfile ID from load_render_profile
minActualDurationNoMinimum total actual duration in ms for a component to appear — render time including its children, the same metric this tool ranks cost by. Filters sub-millisecond noise. Defaults to 0.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.5.2

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It does disclose that the analysis is heuristic and depends on the exported profile, which suggests it is non-mutating and approximate. However, it omits explicit statements about side effects, prerequisites, or reliability limitations, leaving important behavioral traits implied rather than stated.

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?

A single sentence that front-loads the main action (highlight repeated-rerender components) and then states the added value (explain likely causes via heuristics). There is no filler or redundancy.

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

Completeness3/5

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

For a tool with no output schema and no annotations, the description covers the core result type but not enough surrounding context. It does not explain output structure, prerequisites beyond the implicit exported profile, or how this tool relates to the many sibling analysis tools. The schema documents parameters well, but the description remains minimal.

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% for all three parameters, so the schema already documents their meaning. The description adds little param-specific value; the phrase 'exported profile' loosely aligns with profileId, but no additional syntax, defaults, or interactions beyond the schema are described.

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 states a specific verb and resource: highlight components with repeated rerenders and explain likely causes. It is clearly distinct from sibling tools like get_render_summary or get_slow_components because it focuses on rerender diagnosis using heuristics, though it does not explicitly name those siblings.

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?

Usage context is implied by 'derived from the exported profile': an agent can infer this is a post-capture analysis step, likely after load_render_profile. However, the description does not state when to choose this over alternatives such as get_slow_components or compare_renders, nor any conditions where it should not be used.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/souvikdu/perfonext-render-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server