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Totally settling the "MCP vs CLI for coding agents" debate with this humongous blog post. I benchmarked screen, tmux, and a bespoke custom CLI and MCP tool against 3 task that require the agent to steer TUIs (lldb, python repl, opencode)

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Mario Zechner

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65,025 görüntüleme • 11 ay önce •via X (Twitter)

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Today we're open sourcing a technical preview of the GitHub Copilot CLI SDK. Build agents with custom tools in Go, Python, TypeScript, and C#. Built on the same agent loop that powers the Copilot CLI and GitHub Coding Agent. Supports BYOK, and any model. Here is the Copilot CLI driving Excel:

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it really doesnt matter if your agent uses the cli or mcp what really matters is how to best enable ur agents to build autonomously for u without the crossmint cli tool my agent would have to use the browser and get my input in every step. now i just let it run see how i do it

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Okay, Greg Brockman is team CLI all the way. Garry Tan thinks MCPs suck. So we hit the streets of SF to see if the city agreed. We posed a simple question: MCP or CLI? - Basically everyone under the age of 35 said CLI - One person said MCP was as bloated as Java - & unsurprisingly, numerous people told us to touch grass Final score- MCP: 3 vs CLI: 17 SF has spoken, and Composio listened. Our universal CLI is now live! Drop your best CLI vs MCP hot take in the comments and we'll send the best ones some very sick gear 👀 Link to try our CLI in the next thread ⬇️

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Railway's new remote MCP (and the Railway Agent it accesses) are the best way for agents to work with everything in your Railway workspace. We released it last week and Cody De Arkland takes it and the new updates to the Railway CLI for a spin. Check it out 👇

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1:50

this tweet misses the gold of executor! the whole point is you don't want CLI / scripts, you want API / MCP servers in this video i ask executor to configure itself and add an MCP server - it pops up a browser for me to OAuth through based on the MCP elicitation spec

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1:48

New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:

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2:50

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Remote coding agents are now general purpose productivity tools Here I'm using the Todoist MCP server with Replit ⠕ Agent to clean up the reference section of my task list I'm also using it daily to add labels and keep things organized As it would turn out, coding agents are good for more than coding

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1:00

this has been the most requested feature for years now. FlutterFlow MCP is here. you can now bring your agents directly into FlutterFlow and switch between them: Claude Code, Gemini CLI, Codex, or any MCP-compatible client. can’t wait to see what y’all build.

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0:21

The exchange layer for AI agents is here. Agent Trade Kit gives developers 80+ tools via MCP or CLI to build, test, and deploy directly on OKX Exchange. From market data to trade execution, it taps into the full OKX product suite.

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1:06

This is probably the biggest news yet in software going headless, and will bring knowledge work agents to the masses. The new ChatGPT agents have access to any of the tools and data you want to work with, with complete coding and tool use available to them. Here's an example of a custom sales assistant agent uses Box as a knowledge source for accessing enterprise content securely to answer questions and generate new content on the fly. The workflows can obviously vastly far more complex as the agent can use any of the tools within Box available via MCP and CLI. This precisely what agents will start to look like for knowledge work. You'll be able to spin them up in the foreground or background to help augment work. Big opportunity right now for headless platforms, and for all the new builders and designers of these agents in the enterprise.

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