The MCP versus CLI argument should be reframed as Computer vs No-computer argument
I personally get the dunk on MCP. It didn't work last year, with earlier models. Then we saw CLIs perform much better with the same models. And giving access to bash was much simpler!
Models' training then made them better at calling using a shell. CLIs also have native progressive disclosure, due to the way they work
But the most important fact doesn't get pronounced enough IMO
A key factor was that giving a CLI to a model also means you are giving it an entire COMPUTER
The action space of all commands an agent can run on bash is much, much bigger than a few MCP servers
One is a Turing machine, and the other one is basically a REST API. Of course the Turing machine is going to be more powerful, depending on what is at the other end of the API
By that logic, giving an agent access to bash over MCP versus direct access to bash should have the same level of effectiveness, with optimized prompt engineering and long term training. Because the interfaces are equivalent
So the argument is, should we give our agents access to a computer, or not?
It depends on the security requirements and the setup which the agent is supposed to run on. If you are co-hosting the agent on the same machine you are working on, then it is safer to use MCP servers, because it limits the attack surface in case of adversarial attacks
But if you are willing to give the agent its own physical computer, willing to be mindful about the lethal trifecta and the principle of the least privilege, giving it shell access is much more useful
So MCPs win in restricted/local environments, whereas CLIs/shell access win in unrestricted/remote ones
Running an agent locally and safely with shell access requires compartmentalization. This is much heavier compared to installing MCP servers locally, which don't need that. So there is a tendency to use MCP servers locally, e.g. in a work setting
Cloud agents on the other hand are more likely to ship with a computer. Because they are already isolated = no risk, and because it makes them much more useful. So cloud agents will be using both CLIs and MCP servers, whichever gets the job done!
I just registered for an .agent domain and joined the .agent community!
@dutifulbob will have bob.agent if it passes :)
https://t.co/lhK5MQS1sk @agentcommunity_
Sep 2021 @lexfridman podcast with Don Knuth, they also talk about OpenAI Codex (code completion model) around 33 minute mark
This aged very well
https://t.co/O1eTXlHTNC
Codex's long horizon task and instruction following has been the most life-changing AI feature recently
It is unlocking the next level of automation for me. I can convert my own heuristics into prompts and multiply my throughput 100x
Currently spending some thought on how to orchestrate all this. Below is a flowchart from a triage workflow I am working on
This is unscientific, but there are certain keywords and phrases I use a lot while using certain models like openai's. I use them a lot because they get me what I want immediately:
- plainer lang
- cutover
- elegant and production ready
- holy grail
What are yours?
Request for memes
A funny and quirky edit of historical timeline of the madness that is openclaw
with "Chess type beat" or sth equally jazzy/circusy
Preferably including its adventure warelay -> clawdis -> clawdbot -> moltbot -> openclaw
Including:
- its explosion after @4shadowed's discord integration
- naming drama, moltbook and people getting oneshotted about AI takeover
- @steipete speedrunning everything
- andrew tate calling us gay lol
- up to Jensen talking about openclaw on stage for 5 minutes straight
and other things I am forgetting
maybe overlaid with a lobster just keeping climbing the github star graph and breaking it