"Windows Performance Toolkit and xperf.exe" matching MCP servers:

Enables Windows users to connect Antigravity CLI as an MCP subagent for coding tasks such as file reading, code execution, edits, and terminal commands, with model selection, conversation continuity, and streaming progress.

A general-purpose MCP server providing web search, persistent memory storage, and secure code execution capabilities. It enables AI agents to search the web, store and retrieve data, and run Python/JavaScript code in sandboxed environments.

Enables secure Windows development automation by providing MCP tools for filesystem access, project builds, restricted PowerShell commands, and approved network fetches.

Enables AI coding agents to work inside a disposable Windows guest desktop, where they can run shell commands, launch applications, inspect and operate native GUI controls, perform browser DOM actions, and transfer files. Fresh observations, PNG screenshots, and hashed artifacts let agents verify results without touching the host desktop.

Enables AI coding agents to generate standardized code using scaffolding templates, enforce architectural patterns, and validate outputs programmatically. Supports creating projects from boilerplates and adding features to existing codebases while maintaining team conventions.

Enables Windows-native developer orchestration for Claude Code and Codex with PowerShell discovery, capability routing, safety-gated execution, package management, and sandbox-based isolation.

Enables coding agents to work on Windows through persistent PowerShell sessions, surgical file editing, code search, background job execution, and web research while avoiding context-heavy GUI automation.

Provides WebAssembly-based, sandboxed tools for JavaScript execution, binary disassembly, file recovery, steganography, image optimization, data processing, PDF redaction, secret scanning, and semantic search.

An MCP server providing tools for read-only SQL queries, REST API calls, sandboxed Python execution, and resource lifecycle management, enabling multi-step research and data tasks.

A serverless-accelerated hybrid development platform that minimizes dependencies in the local development environment and organically combines a virtual operating system kernel inside a web browser with the local host resources.

Connects Claude Desktop to Windows Calculator, enabling accurate mathematical calculations using Windows' native PowerShell calculation engine.

A Windows-compatible Model Context Protocol server that enables AI assistants to interact with Google's Gemini CLI, supporting file analysis, large context windows, and safe code execution.

Enables step-through debugging for C#, Node.js/TypeScript, Python, and Dart applications on Windows through a unified MCP interface. Acts as a bridge between MCP clients and various debug adapters, providing consistent debugging workflows with breakpoints, variable inspection, and process attachment capabilities.

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

Enables Claude Code to spawn child sessions for parallel, asynchronous task execution, allowing users to continue working while tasks run in the background.

Converts Figma designs to React Native components, allowing users to extract components from Figma designs and generate corresponding React Native components with proper typing and styling.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

A Model Context Protocol server that enables Claude AI to interact with Paybyrd's payment processing API, allowing for creating payment links, processing refunds, and retrieving order information.

A Model Context Protocol server that enables interaction with PostgreSQL databases for analyzing setups, debugging issues, managing schemas, migrating data, and monitoring performance.

A local Model Context Protocol server that allows LLMs to securely execute shell commands on remote Linux and Windows systems via SSH connections.

Enables executing Bash commands, pipelines, and scripts across Windows, macOS, and Linux via MCP, with support for multiple runtimes, timeouts, working directories, and stream capture.

An MCP server that grants AI agents unrestricted file system, Python, and PowerShell access on Windows for real, unfiltered automation.

A minimal MCP Server that provides Claude AI models with the 'think' tool capability, enabling better performance on complex reasoning tasks by allowing the model to pause during response generation for additional thinking steps.

Multi-Agent Mesh Network MCP server that spawns specialized AI agents working in parallel to solve complex coding problems, providing 3.64x faster performance through distributed intelligence.

Enables building and cleaning Delphi projects (.dproj/.groupproj) on Windows using MSBuild with RAD Studio environment initialization. Supports both individual projects and group projects with configurable build configurations and platforms.

Enables AI assistants to perform high-performance 3D CAD design, ultra-fast multi-view rendering, immutable versioned project management, and geometry/mesh verification for 3D printing on Windows.

Exposes vLLM capabilities to AI assistants, enabling chat completions, model management, and platform-aware container control with automatic detection of Docker/Podman and GPU availability across Linux, macOS, and Windows.

Zero-setup safety toolkit for AI coding agents with 16 built-in tools for context gathering, safe file editing, validation, and session memory. Features rollback, circuit breaker, sandbox, timeout, and dangerous pattern blocking — no config, no API key, no database required.

Enables AI assistants to leverage Qwen's code analysis capabilities with large context windows, supporting file/directory analysis, sandbox execution, and multiple approval modes for safe code operations.

Provides a universal bridge to interact with any OpenAI-compatible LLM API (local or cloud), enabling model testing, benchmarking, quality evaluation, and chat operations with performance metrics.