Pi now supports MCP. Why we changed our minds, what changed in MCP and in Pi, and what Codemode is.
349 comments
So even with a local Qwen and Pi you can now say things like:
Set up Clop to optimise any PNG that I drop in my website assets folder and convert to a webp with the same name near it
Get Crank to start Time Machine backups immediately when I connect my HDD and notify me when the backup is done.
I want to be able to hold rcmd and fuzzy search and focus cmux agent panes
You would need a much more capable coding model to code those tools from scratch and get the same fail-safe logic that the apps have honed over the years.
Like, since MCP, Crank [1] has fully replaced my use of crontab, launchd, scattered scripts I run once a week. Not that it could not do that before, but it's so much simpler now to just describe the automation and have it happen reliably and visible in the UI. The friction is gone.
[0] https://reddit.com/r/macapps/comments/1wkv0dy/mcp_in_macos_a...
Yesterday I received a new thermometer for my aquarium to replace an old broken one. Both were bluetooth, but different models. I just told claude "I'm going to set up up my new bluetooth thermometer for my fish tank in a few minutes, keep an eye out for it and replace the old broken one with it in Home Assistant" and then walked away and put a battery in it and put it in my aquarium.
When I came back it had found it, replaced all my existing entities for the broken one with the new one, and verified it was all working with my existing graphs and automations.
Recently I wanted to set up a slightly complex routine involving some lights and a couple of motion sensors. It feels like magic to be able to describe the behavior I want, briefly discuss the implementation, and walk past the sensor and see it in action.
User will interact or build apps with simply text like: "Give me all the issues that are X, context: https://somedomain.com/llm.txt"
llm.txt will have all the API instructions
Having an agent keep an eye on stuff and fix things proactively should make the experience much better. Plus I can no longer write yamls at last.
They're so powerful and yet get out of your way when you're not using them. I couldn't imagine being without them. Thanks y'all!
But in my case, a CLI was not enough.
Like, to the MCP I might say:
Set Clop to make every video copied in ~/shots smaller, 2x and silent
By smaller, you mean re-encode to compress file size (factor can be 0 to 100 max compression) or downscale resolution (100% same size, 50% half size)?
And does 2x mean faster speed? In which case do you want to keep frames so the video plays smoother or drop frames for size? Or does 2x mean upscale?
With the CLI I have to first read, learn and memorize the requests and commands needed for each app, the accepted values and formats and the steps to reach a specific result.
There's only so much space in my head I can leave for implementation details of arbitrary apps. I'd rather have an agent care about that.
And yes I get the irony, those are my apps, I coded them by hand for years, I should know their implementation details, yet even I forget if I should pass 50% or 0.5 for half size.
Btw Clop is a media file compressor for context: https://lowtechguys.com/clop
This seems like exactly the sort of thing I've done with shell scripts or even makefiles.
But this is for people that already use the app, researchers, writers, students, people that aren't necessarily comfortable with a terminal. And given Clop already implements the basics: an efficient file events watcher, tuned encoders for the Mac silicon, fail safe backups and UI for seeing the result and interacting with it in real time, it has advantages over trying to do it yourself.
Why is AI involved for any other reason than building the original test implementation?
Not sure if you got the right context, your question doesn't really make sense to me.
We're back onto the original use cases for natural language processing. This is where all the value always was, and now the market has proven to itself what anyone with even a bachelor's in computer science already knew.
The linked post from Armin is gold:
"... whenever you are confronted with a very strong opinion about a topic, reasonable discussions about the topic often involve arguments that have long become outdated or are no longer strictly relevant to the conversation."
(https://lucumr.pocoo.org/2016/11/5/be-careful-about-what-you...)
And that's from 2016! These days if you're arguing from a position you took even a week ago, you already might be out of sync.
Thats my observation when people retort “whataboutism” in usually a geopolitical context
Its not ever clear to me that people are aware that their own country or a place they respect engages in the same practice as the place they are denigrating
Like, sure I would like both places to fix their problem but dont you have better things to do like fix your own?
A direct quote from March, 2026[1]:
> If you’re still not convinced that a lot of this discourse [regarding the death of MCP] lacks nuance and is just hype, congrats on buying into the current AI-influencer FOMO hype cycle; see you in 6 months when the influencers move on to the next revelation of the moment to stay relevant and get your eyeballs and dollars.
My biggest complaint right now is that OpenAI has still refused to implement the MCP Prompts spec[2] and in general, the major clients have spotty implementation for some of the features in the spec.
[0] https://news.ycombinator.com/item?id=47380270
[1] https://chrlschn.dev/blog/2026/03/mcp-is-dead-long-live-mcp/
I follow several influencers from pre-AI times who were (or were trying to become) social influencers thought leader types. People like Theo or many of the JavaScript and training course people. Following them was helpful to follow the trends that more chronically online juniors would be picking up and pushing at the workplace, which set me up in a better position to understand and then defend against it.
All of them, every single one, have dropped their previous influencer topic and pivoted to being AI influencer. Every time I see a post they’re either saying you need to adopt a new trend or that last month’s trend is dead. “Prompting is dead! Graphs are the future!” or “Claude Code is OVER! This new harness is 10X better”
MCP was one of these topics. Everyone went from telling you that you needed to use MCP or be left behind, to declaring that MCP was dead almost in unison.
The only pro-MCP holdouts were the influencers who had built their own MCP courses for sale.
MCP servers provide three things: tools, resources, and prompts. Of these, tools seem to be the only part implemented consistently across major clients like ChatGPT, Claude.ai, Claude Code, etc.
For prompts and resources, there doesn't seem to be a common understanding of how clients are supposed to consume them.
For example, if an MCP server exposes resources, Claude Code can discover them and consume them when needed without you explicitly asking for a specific resource. Claude.ai behaves differently. It doesn't automatically discover and consume those resources. Instead, it gives you a way to manually add an MCP resource to the prompt.
So while MCP defines tools, resources, and prompts at the protocol level, the actual user experience for resources and prompts varies quite a bit across clients.
Codex is the only mainstream harness that does not implement this in the client.
A good use case for resources is small amounts of commonly needed state that can be fetched and proactively updated by the mcp server, saving latency when the model requests it.
I can see the snap appeal. One protocol, we can chuck an auth reverse proxy in front of all the MCPs, compliance has their integration point, etc.
I don’t think MCP is structured enough to give a huge edge over bash there. Looking at MCP messages, they aren’t immediately more legible than a bash command, output and exit code. You also don’t own a lot of the MCP servers you use, so backtracking for audits will require knowing what MCP commands did what back then.
I do suspect something more like MCP than bash will be the winner. MCP just feels very open source rather than enterprise. Eg I don’t think I’ve seen any sort of privilege escalation and logging scheme. The enterprise will want some sort of “request admin privileges” scheme. Likewise they’ll probably want more context on ACP requests; who is calling this MCP, using what agent, and for what project?
MCP over HTTP buys you server side telemetry, composability, remotely held credentials (security), etc.
MCP is about enterprise control of the server side; no advantages on the client side at all.
I do agree, the "MCPs are dead" narrative was overblown, but there were legit reasons we weren't ready to go all in on them back then.
It’s suboptimal for the reasons the author outlines: but so is USB-C. So is NVME, so is HDMI.
We use these hugely successful technologies in spite of their flaws because they’re widely compatible and easy for the end user.
That’s why MCP is everywhere. It might not be performant, robust and uniform but it WILL get better over time.
And I’d much rather have the broad MCP ecosystem that we have now than seven or eight different “optimal” ways of plugging in an LLM to something useful.
I hope they'll do the same and eventually add native support for ACP (https://agentclientprotocol.com/get-started/introduction) which, on the contrary, I use quite.
Then again, I don’t even know if general adoption is what Pi/Earendil is going for.
I'm not so sure about this move, or the general inclusion of code mode in the core editor as one of pi's main selling points was its minimal nature.
Though as time progresses, they are probably going to do the same with sub-agents.
Imagine a world where you could:
* Configure your favorite harness/chat client with any OpenAPI spec for an API that supports Oauth2.
* The harness would walk you through the Oauth flow and securely store the token.
* And then insert some tools for discovering the API methods and making requests in to the context.
* The agent could then formulate a request, call the request tool, and the harness would 1) makes sure it's allowed to make a request to that API, and 2) insert the Auth Token into the request.
It would be basically exactly the same way MCP is setup today, except all you would need is an OpenAPI spec. You wouldn't have setup a server for a janky new standard that's half implemented slightly differently by every harness/chat client.
I suspect that a smart model driving multiple dumber models for work and then using sub-agents with the same smart model for adversarial review will be a pretty common pattern.
Personally, I got a bit confused about Pi having most of that stuff as plugins since I remember how much of a mess Eclipse was where so much was just loosely fitting together plugins and just went with OpenCode since it covers most of my needs out of the box. Guess that might also be a sign of me getting older, because my IDEs and desktop environments are all closer to stock too.
Using sub-agents for example also lets me decrease the default context size in Claude Code instead of running at the full 1M like:
/autocompact 420k
Same idea with something like OpenCode, there I even configured custom agents for review: https://opencode.ai/docs/agents/
https://github.com/can1357/oh-my-pi
I haven't tried it much though, can't vouch how well it works.
On top of that, somewhat unrelated I’ll agree but still, it has support for vim keybindings
I did create some extensions where it spawns sub agents for specific tasks, especially when I want to keep the context clean or when I really want to offload a piece of work to a cheaper model. And for that I have a high degree of control over, I know which model is being used for each subtask.
I find Claude Code too unwieldy for my tastes. Pi's philosophy of being very light on features nut highly flexible for customization, clicked very well for the way I work.
Like sub-agents, you could just instruct pi/any harness with a user prompt/system prompt to start new invocations of itself, if you share what the exact command is, and pi or any other harness will do their own poor man's version of sub-agent via standard unix programs.
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