"Debugging WebRTC SDK Implementation Issues in Visual Studio 2019" matching MCP servers:

A server that enables retrieval of Sentry issues through two simple tools - get a specific issue by URL/ID or get a list of issues from a project.

Persistent memory and pattern learning for AI coding assistants via MCP.

Enables AI clients to write, run, and visually render code in a single loop, combining secure execution via Judge0/Codebox with Playwright screenshots.

Enables AI assistants to directly manage Roblox Studio projects by creating, reading, updating, and deleting scripts, listing instances, executing Luau code, and inspecting properties. It works through natural language, making Studio operations accessible to AI.

A server that integrates Flux's advanced image generation and manipulation features into AI coding assistants, enabling seamless text-to-image and image control workflows in IDEs like Cursor and Windsurf.

Enables AI agents to interact with the Roark API by writing and executing TypeScript SDK code in an isolated sandbox, with built-in documentation search to guide those tasks.

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.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

Exposes Vercel AI SDK Core capabilities (generateObject, generateText, streamText, UI generation) to AI development environments like Cursor, designed to work in orchestration with other MCP servers for multi-step AI workflows.

An MCP server that runs a quality gate on generated code, executing it in a sandbox and scoring it before returning the code to the user.

A Python implementation of the Model Context Protocol that enables applications to provide standardized context for LLMs, allowing developers to build servers that expose data and functionality to LLM applications.

A Python implementation of the Model Context Protocol that allows applications to provide standardized context for LLMs, enabling creation of servers that expose data and functionality to LLM applications through resources, tools, and prompts.

A GitHub-based implementation of the Model Context Protocol that enables LLMs to access and manipulate data in a Universal Object Reference (UOR) framework, providing standardized interfaces for object management with decentralized storage.

A Model Context Protocol server that connects to Google AI Studio/Gemini API, enabling content generation with support for various file types, conversation history, and system prompts.

An SSE (Server-Sent Events) server that leverages OKX DEX SDK to support DEX trading operations on Solana blockchain and cross-chain bridge transactions.

A Python framework for building MCP servers with modular architecture, dependency injection, and built-in authentication. Enables creating scalable, testable MCP services with features like pipeline interceptors and background tasks.

A TypeScript wrapper library for the Model Context Protocol SDK that provides a simplified interface for creating MCP servers with tools, resources, and prompts without needing to work directly with the protocol.

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.

MCP server that exposes a pool of Claude SDK agents as tools, enabling deterministic agent creation, retrieval, and resumption from a capability corpus.

Enables automatic weather information retrieval through a custom MCP server integrated with OpenAI using Cloudflare tunnels. Demonstrates seamless function calling between OpenAI and custom MCP tools without manual intervention.