"How to use Canva" matching MCP servers:

A local MCP server that lets compatible agents use the official, signed Computer Use broker bundled with the OpenAI ChatGPT macOS app.

Browser use using Typesafe's Jev model

Enables agents using Computer Use to inspect expected browser JavaScript dialogs and respond to OK/Cancel confirmations or text prompts without user intervention. Unexpected dialogs still interrupt the workflow.

Enables Claude to delegate tasks to OpenAI expert models (GPT-5.3-Codex and GPT-5.5) as subagents, with orchestration patterns for safe and effective use.

Lets a model use hundreds or thousands of MCP tools without loading them: it puts five tools in front of a large MCP server or gateway, so the model searches for the tool it needs and calls it. Search combines BM25 with a multilingual embedding model that runs inside the proxy.

A lightweight, zero-dependency Python MCP server that exposes a single do_everything tool. Any AI agent that supports MCP can use it to offload all language-model work to a local OpenAI-compatible endpoint, reducing cost on the agent's primary LLM.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

Enables ChatGPT web to use local tools like file reading, command execution, and patch application through an MCP server over OpenAI Secure MCP Tunnel.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Enables coding agents to ask what a window shows and receive a concise JSON answer from a local Ollama model instead of ingesting the full accessibility tree, reducing token usage. It is read-only and supports optional session context, health checks, and model release.

Enables routing tasks to the right specialist agents, assembling the needed context from a layered catalog of agents, skills, knowledge, runbooks, topics, tools, and connectors, while remembering how a business wants work done.

Use your existing Firefox and logged-in tabs, limited to tabs or tab groups you explicitly share.

Enables low-cost agent models to control Windows applications through a compact, state-safe proxy over Open Computer Use, reducing model-visible context by up to 99.8% with support for record/replay and reusable UI component memory.

Enables coding agents to drive a real Chrome browser to complete natural-language web tasks and return evidence for verification.

Teach any AI agent how you use an MCP server – Soft-Landing to your AI integrations

Enables agents to discover, read, and use reusable skills stored in public GitHub repositories.

Enables any MCP client or OpenAI-compatible application to use Meta Muse through a logged-in Chrome session, with tools for chat, attachments, session management, media retrieval, streaming, and tool-call compatibility.

Enables Cursor to drive Google Chrome through the jev-browser-use click loop, with Cursor supplying tasks, typing text, and verifying results while Jev chooses the next click.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Let Claude Code, Codex and any AI agent use the Chrome you're already signed in to. Open-source CLI + MCP server + Chrome extension (native messaging, no debug port); stealth by default.

The first open-source MCP server that enables AI to fully control remote macOS systems.

MCP server enabling AI agents to control a real Linux browser with live view, human takeover, and safety guardrails.

A command-line tool that enables the use of MCP with the Room protocol, allowing agents to create and interact in peer-to-peer virtual rooms for goal-oriented collaboration.

A Model Context Protocol (MCP) server that lets you seamlessly use OpenAI's models right from Claude.

A tool that allows Claude Code to use Gemini AI as an MCP server, leveraging Gemini's large context window for analyzing large files while saving Claude Code tokens.

Enables an AI to delegate work to secondary Antigravity CLI accounts, running jobs in parallel with dependency (DAG) scheduling, file read/write declarations, warm multi-turn sessions, account quota tracking and compact result collection. Users simply describe their request in natural language while the AI plans and the server executes — no hand-written workflow JSON required.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

An MCP server that provides web search capabilities through the Tavily API and weather data retrieval tools. It demonstrates how to integrate external APIs into AI applications and build agentic workflows with LangGraph.

A Model Context Protocol (MCP) server that demonstrates how to build and implement custom tools for Claude using the mcp-framework.

TypeScript implementation of the Model Context Protocol that standardizes how LLMs connect to data sources and tools, eliminating vendor lock-in and simplifying AI integration.

An MCP server that allows Claude models to use Union tasks, workflows, and apps as tools in conversations.

Enables running and monitoring 19 agentic business use-case engines with MCP orchestration, memory evolution, and approval gates.

Enables AI agents to use Scalebrowser's isolated, persistent-identity browsers on the user's own machine, handling logins, challenges, and page interactions over MCP.

Facilitates browser automation with custom capabilities and agent-based interactions, integrated through the browser-use library.

A ready-to-use starter implementation of the Model Context Protocol (MCP) server that enables applications to provide standardized context for LLMs with sample resources, tools, and prompts.

A joke/demo Model Context Protocol server that injects cringe-worthy advertisements into LLM responses, showcasing both how to build MCP servers and the risks of ad-injecting intermediaries.

Lets local MCP clients use one LightNow-managed MCP entry instead of storing every MCP server configuration and secret in every client.

Enables AI agents to coordinate atomic distributed transactions across a swarm through a prepare/vote phase, unanimous commit-or-abort consensus, quorum validation, and failure recovery. It also layers in vector-clock causal stamping, LWW CRDT reconciliation, and gossip dissemination so multi-node state converges deterministically without external dependencies.

Recommends APIs to AI agents based on agent-readiness and use-case keyword overlap, returning structured endpoints and documentation to ground integration code.

Human in the loop for AI agents. Sends a decision an agent is unsure of to several ID verified people and returns their consensus and how strongly they agreed.