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    Zero-sidecar MCP server embedded directly in the Godot 4 editor as a GDScript EditorPlugin — no Node or Python sidecar. Reflection-driven tools over any engine class, validate-before-write GDScript, scene/script/resource authoring, and a runtime play-test loop (play, screenshot, input, assert).
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    MIT
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    Enables LLM agents to programmatically inspect, debug, and test other MCP servers by wrapping the MCP Inspector CLI. Supports listing and calling tools, reading resources, and testing prompts on both local and remote MCP servers.
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    MIT
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    A high-performance, multi-protocol API mock server with 18 built-in MCP tools for managing HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP mocks, chaos engineering, stateful CRUD resources, and request verification.
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    Apache 2.0
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    Connects AI coding assistants to TestCollab for managing test cases, plans, and suites directly through natural language. It enables users to create, update, and query testing resources within integrated development environments and AI chat clients.
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    A specialized testing harness that enables AI assistants to thoroughly test other MCP servers by connecting to them, discovering their tools/resources/prompts, executing test calls, and performing end-to-end validation with LLM integration.
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    MIT
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    Enables AI assistants to debug JavaScript and TypeScript applications by connecting to Chrome DevTools Protocol-compatible debuggers, allowing them to set breakpoints, step through code, inspect variables, and evaluate expressions with full source map support.
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    Apache 2.0
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    Enables LLMs to inspect and test other MCP servers by listing and calling their tools, reading resources, and getting prompts. Supports stdio, SSE, and HTTP transports for both local and remote MCP server inspection.
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    MIT
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    Provides programmatic access to BlazeMeter's performance testing platform through MCP tools. Enables users to retrieve test runs, analyze performance data, view error reports, and manage testing resources via natural language interactions.
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    Enables automated access to LoadRunner Cloud APIs for retrieving performance test data, managing projects, and collecting test results. Supports integration with AI clients for building performance engineering workflows and dashboards.
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    A testing server that demonstrates Model Context Protocol features, providing access to user data, todos, and system information through resources, tools for user management and calculations, and prompt templates for various analyses.
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    An MCP server for WCAG accessibility auditing in AI coding agents, providing tools to audit HTML, files, URLs, and diffs, plus a prompt for React component auditing.
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    MIT