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Vinny
@hot_town
Creator @ Yapper @
1.3K Following    6.5K Followers
In 5 months, software factories will be like the Epstein files. Every will have forgotten about em.
just had a landscaper tell me “buffalo grass is the OG of lawn grasses”
just heard a man order a pastry by saying "imma say what's up to this bread over here"
'Lichen Trip' A new song by us (@Bibio & Dorian Concept) Out now via @WarpRecords
“one-shotting it” is what me and the boys used to call taking a dump where it all came out in one peice
Get a load of this joker over here. (A/B testing thumbnails 😆)
A must read. Steve killed it here. I even had to look up eschatological.
Debate over. The winner is… an API ?????
the right answer here is to make an OpenAPI spec and convert that into a CLI and an MCP
Let's settle the MCP server vs. CLI debate. Here's a list of their pros and cons👇 MCP servers: pros > Typed discovery: schemas tell the model exactly what exists and how to call it (Tool Search makes this cheap in most harnesses). > Structured args, no shell quoting, which sidesteps the #1# shell-agent failure mode (nested quotes). > Credential isolation: auth lives in the server/bindings, never in session text. > Works for services with no CLI (SaaS APIs, browser pages, WebMCP). > Per-call, inspectable dispatch that fits approval-per-action models. > Uniform transport/auth across clients; harness-agnostic. MCP servers: cons > Needs a running server plus protocol layer; another moving part. > Code mode over MCP needs a sandbox and coarsens permissions. > Not reachable from the agent's shell; no bridge into Bash/pipes. CLIs: pros > Bash already is code mode: pipe, loop, filter, return only the answer, no new protocol or sandbox. > Composable with the whole Unix toolbox (jq, grep, xargs). > Already OS-sandboxed (Seatbelt in MacOS / bubblewrap in Linux ). > Zero extra infra if the tool ships a binary; fast to adopt. > Great fit for exploratory/debugging work where the model needs to see intermediates. CLIs: cons > Discovery is --help prose, not a schema; success depends on doc quality. > Quoting/escaping errors, prompts, pagers, TTY. > Credentials sit in env/config the shell can read, a leak surface. > Untrusted output steering shell commands is injection.
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This makes WebMCP even more important to learn:
Claude now has its own built-in browser in Cowork. When your task involves a website, a browser opens in Cowork's side panel, and Claude navigates, fills forms, and finishes the job.
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If your agent sells stuff to other agents do you still have to pay taxes on it?
Good ideas multiply when you act on them.
New personal strategy: Ignore all tech/twitter trends that don't show some promise of long-term adoption. Focus solely on the ones that do.
I think all sites will use WebMCP in the future. Agents using your site are MUCH faster with it. Plus, it opens up the door for new, creative interactions:
who's gonna do the butt tattoo version of this?
I'm selling ad space on my MacBook → 10 sticker spots on the lid → live auction → 14 days except I don't own it yet, the auction buys it → your logo travels with me and gets seen both online and IRL
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This makes WebMCP even more important to learn:
Claude now has its own built-in browser in Cowork. When your task involves a website, a browser opens in Cowork's side panel, and Claude navigates, fills forms, and finishes the job.
Show more
Yes! Here's my node-based UI on top of LLMs with WebMCP so I can: > dive deep into topics with my agent of choice > keep all the context in my daily-driver agent (not the app) > easily spin off new nodes > traverse the node tree at a glance TONS of usecases where a UI makes sense in collab with an agent. This is just one!
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Really interesting new blog post from @openai for several reasons: 1) Shows an example of building with WebMCP, meant for when you want agents and and humans to collaborate on using a UI (like co-editing notebook cells). It's different than MCPs or APIs in that its exposed directly through the browser. Read the post for discussion of the tradeoffs. 2) They created a new kind of notebook which works with WebMCP that prioritizes meeting people where they are: you bring your own coding agent and files are just markdown. The author uses it to curate runbooks or high quality examples of how to run foundation model evals on their infrastructure. Notebooks are good for this since they require tinkering with state of long running jobs interactively while taking notes inline. And its open source ✨ Blog: P.S. this post is authored by Jeremy Lewi who isn't on X but here is his website
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Wanna learn more about WebMCP? Now that OpenAI is integrating it into ChatGPT, you should. Greg and I get into it, along with the potential for entrepreneurs to utilize this tech to their advantage: