"Optimizing and Improving Flutter Application Performance" matching MCP servers:

Performance AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

A comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

AI job search and job application tracker. Search live jobs by title, location, salary, date posted, and remote or on-site, and see each one checked on real data: pay against market rates, ghost-job signals, visa sponsorship history, and how well it matches your resume. Check how hiring software reads your resume, track applications, set follow-up reminders, and get email alerts.

This MCP wraps Bitrefill public API to allow agents to search for products and shop using cryptocurrencies like Bitcoin, Ethereum, Solana, and many more.

Credit and payments for AI agent developers — over MCP. No crypto required

Connect AI agents like Claude, Cursor, and Gemini to historical Windows performance and privacy data gathered by the AppControl Windows app. This server enables natural language queries into CPU, GPU, and temperature history alongside system security events for deep local auditing.

MCP server for answering questions about official statistics from a single publication URL, with tools to check query scope, retrieve overview, text, data files, and search.

Lets any MCP-compatible AI agent search live resort inventory, request exact all-in quotes including transfers, and start real hotel bookings that the traveler completes on a hosted Stripe checkout.

Provides persistent, self-optimizing memory for AI agents, enabling them to remember preferences and context across sessions and share knowledge across multiple agents.

Protects AI agents from prompt injection and destructive actions while enabling self-improving prompts through a security pipeline.

Enables LLMs to query telemetry data via the Spyglass AI agent, providing intelligent insights about application performance, errors, and bottlenecks.

A Model Context Protocol server that lets AI assistants interact with the Sentry API to retrieve and analyze error data, manage projects, and monitor application performance.

lets you interact with your meeting data (to list, ask, summarize, extract - virtually anything about your meeting) through Claude’s desktop client across Zoom, Google Meet and MS Teams via tl;dv.

Enables large language models to retrieve up-to-date and correct information about dlt pipelines, datasets, and schemas, improving AI-assisted development.

Enables building, publishing, and improving PWA games from your editor by scaffolding games, updating files, and auto-deploying to a live URL.

Exposes Amazon Nova Act web automation capabilities through the Model Context Protocol, enabling AI agents to perform browser tasks like navigation, data extraction, and form interaction.

Enables multi-agent code review with cross-verification of findings against source code, catching hallucinations and improving agent accuracy over time.

Enables building, optimizing, reviewing, and running AI agents and skills, plus managing authorized work items, in Erstan's QA environment via OAuth-authenticated MCP.

The optimizing compiler for agentic tools