mcp-perf-tools
Provides performance analysis tools for AI agents, including JavaScript benchmarking, memory analysis, complexity estimation, bundle analysis, and load testing.
README
mcp-perf-tools
Performance analysis tools for AI agents, exposed via the Model Context Protocol (MCP).
Tools
benchmark
Benchmark JavaScript code execution. Run a snippet N times and measure min/max/avg/median/p95/p99 latency and operations per second. Optionally compare two implementations side by side.
Parameters:
code(string) — JavaScript code to benchmarkiterations(number, default 1000) — Number of iterationscompareCode(string, optional) — Second implementation to comparelabelA/labelB(string) — Labels for comparison output
memory_analyze
Analyze Node.js memory usage: heap used/total, RSS, external memory, and array buffers. Takes snapshots over time and uses linear regression to detect trends and potential memory leaks.
Parameters:
action—"snapshot"|"analyze"|"clear"
big_o_estimate
Estimate Big O complexity from empirical timing data. Fits measurements against O(1), O(log n), O(n), O(n log n), O(n^2), O(n^3), and O(2^n) using R-squared scoring. Includes an ASCII growth curve visualization.
Parameters:
inputSizes(number[]) — Array of input sizesexecutionTimesMs(number[]) — Corresponding execution times in ms
bundle_analyze
Analyze a JavaScript bundle file: raw size, gzip compressed estimate, detected module count, largest modules, and tree-shaking opportunities (side effects, duplicates).
Parameters:
filePath(string) — Absolute path to the bundle file
load_test
Simple HTTP load tester. Sends N requests at a given concurrency level and reports response time percentiles, error rate, throughput (req/sec), and status code distribution.
Parameters:
url(string) — Target URLtotalRequests(number, default 100) — Total requests to sendconcurrency(number, default 10) — Concurrent request countmethod(string, default "GET") — HTTP methodheaders(object, optional) — HTTP headersbody(string, optional) — Request bodytimeoutMs(number, default 30000) — Request timeout
Setup
npm install
npm run build
Usage with Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"perf-tools": {
"command": "node",
"args": ["D:/products/mcp-servers/mcp-perf-tools/dist/index.js"]
}
}
}
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.