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

Peer-to-peer WebRTC communication for AI agents, connecting autonomous coding agents over low-latency WebRTC DataChannels with room-based signaling, video stream bridging, and multi-agent coordination — all exposed as MCP tools.

Enables agents to submit precise visual directions by selecting interface elements, delivering versioned intent envelopes for human-verified changes.

A two-sided marketplace that enables AI agents to buy and sell datasets, prompt packs, and MCP tools using Bitcoin Lightning for instant settlement. It provides agents with tools to manage local stores, publish products globally, and earn credits through a specialized economy.

Enables AI coding agents to see and interact with real Chrome pages through structured DOM inspection, targeted screenshots, recordings, and human-in-the-loop approvals across major coding-agent hosts.

Enables existing agents to access browser automation, Office document generation and conversion, terminal and code execution, charts, knowledge retrieval, media, computer control, maps, data, and integration tools through one MCP server with local runtime setup.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Enables LLM agents to orchestrate a film production pipeline from brief to final cut, including shot planning, rendering, quality control, and assembly, using block-method planning and style-drift QC.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables Claude Code to control Firefox through tools for tabs, navigation, clicks, typing, scrolling, screenshots, page reading, forms, JavaScript, and console/network logs.

A TypeScript SDK for building MCP servers and clients, providing standardized context provision for LLMs through tools, resources, and prompts.

Enables users to describe an LLM fine-tuning workload once and receive ranked, task-aware GPU recommendations across a dozen cloud providers based on required VRAM/FLOPs, cost, and runtime. It surfaces the cheapest, fastest, and balanced options through MCP so coding assistants can plan training hardware without manual price comparison.

It enables Microsoft Copilot Studio agents to connect to and use MCP-based tools, such as fetching jokes, through an Azure-deployed server and Power Platform connector.

Acts as a broker that lets an MCP client drive multiple Desktop Commander workers, with automatic connection recovery and protection against file writes colliding across sessions. It also provides a Windows setup/dashboard for installing dependencies, registering workspaces, starting the OpenAI tunnel, and monitoring workers, sessions, queues, and recent events.

Enables AI assistants to interact with the YOSO marketplace for hiring agents, managing jobs, and optional Hyperliquid trading. Provides tools for marketplace operations, job lifecycle management, and trading functions for agents offering trading services.

Enables local opencode agents to control a live Chrome browser via MCP tools, including tab management, JavaScript execution, clicking, form filling, page reading, screenshots, and console log retrieval.

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.

Exposes ChatATP Studio's backend API as MCP tools over Streamable HTTP, enabling clients to manage agents, knowledge bases, MCP connections, HTTP APIs, LLM providers, messaging platforms, and teams with forwarded authorization.

Universal governance layer for AI agents — MCP-native, fail-closed, LNN interpretability. Governed receipts, IPFS audit proofs, and rollback for any agent in any framework.

Connects agentic platforms to one or more local or networked LM Studio instances, exposing chat, embeddings, model listing, health, and pool-status tools. Provides intelligent load balancing, automatic failover with circuit breaking, role-based routing, and a daemon mode with a real-time web dashboard and HTTP/SSE endpoints.

Gives any MCP agent a real Android phone in the cloud: a device modelled on a real model, Google Play, a network in the country you choose, snapshots to reset between runs. Four tools: devices, observe, act, snapshots.

Enables coding agents to compose, edit and run multi-agent pipelines represented as songs, where channels are agents, notes are agent calls, and mixer buses carry each agent's output to the next. Lets agents create and modify arrangements, validate and render projects headlessly, play them back live in a studio window, and export the result as WAV or MP3, with every change undoable and cached takes replayed for free.

Enables MCP clients to discover and connect over MQTT, list and invoke tools, and read resources in browser and Node.js environments.

Enables Claude Code, Codex, Devin, or any MCP client to control Chrome/Edge through the repository's browser extensions, with Claude-style visual tools or Codex-style text-first tools.

A lab demonstrating how to deploy a Model Context Protocol (MCP) server and integrate it with Microsoft Copilot Studio, allowing users to connect AI models to different data sources and tools through a standardized protocol.

Enables AI agents to post tasks with JSON-schema validation and run workers, facilitating agent-to-agent collaboration on the NexusToken network.

Enables autonomous agents and MCP-compatible clients to enforce policy-approved actions using risk tiers, reversible checkpoints, and token approval bounds.

A server implementing the Model Context Protocol (MCP) that delivers jokes upon request, demonstrating how to connect AI models to data sources and tools within Microsoft Copilot Studio.

Turns Claude Code into an AI Agent Studio with a guided menu and 11 tools to design, create, and manage multi-agent projects without coding.

Turns any OpenAPI/Swagger spec (JSON, YAML, or URL) into a production-ready, type-safe FastMCP Python server with visual endpoint selection and 1-click Claude Desktop or Cursor IDE integration.