← Back to context

Comment by mike-cardwell

4 days ago

I gave claude an API key for Home Assistant. I can tell it to create dashboards, set up automations, diagnose problems etc, all using natural language. No MCP needed.

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.

MCP is a tool more for security than anything else. If you give your agents access to an API key, there's a chance they can accidentally or maliciously leak that key. If the MCP server has access to the keys instead, it takes that possibility away. That's not always something you need to care about, but it is very important for some people's threat model.

  • > MCP is a tool more for security than anything else. +1 to this; API keys mean: a) Your agents are overprivileged by default b) Your API key is more likely to get into logs and pre-training / leaked as FrinkleFrankie mentioned c) You can't manage it centrally with granular tool policies in Enterprises. (e.g. "you're not allowed to read slack channel for #finances")

    Also, you can always collapse MCP to CLI, so MCP as auth/security middleware makes a lot of sense.

    PoC of MCP -> CLI: https://github.com/edison-watch/cli

  • > MCP is a tool more for security than anything else.

    The agent can get to the resource through the MCP server or using API key. I personally do not see the benefit MCP is providing here. Sure you can reduce the exposed surface at MCP layer, but I do that at the API layer. I don't need to add another layer here.

    I can kinda understand if you do not have control of the API layer and/or you have to expose the API layer to the public Internet as well. Most of the time that is not the case for me.

  • Sooo, how does the agent authenticate with the MCP server?

    • My own approach is to put the API key in the MCP server, apply principle of least privilege there, and firewall access to MCP with agents being on same private network with Tailscale.

      Not only giving an API key to an agent can leak to the model because of harness issues or too broad reading rights, but also most providers don't give the ability to apply principle of least privilege to an API key.

      I don't want to give an agent full R/W access to any of my services/accounts.

    • The agent doesn't, the harness does. It's separate from a normal conversation / agent runtime environment. How do you suspect auth keys can leak from an MCP that's been added to chatgpt.com?

    • With a different key, obviously. This lets you keep the MCP server firewalled to your local network only while still allowing home assistant itself to access the internet

    • You give it a key of course! And if that doesn’t fit your security model and threat vectors, simply give the key to another MCP.

I +1 this approach. We are doing similarly. Instead of providing MCP, we are simply providing API key and documentation. Folks are able to then just paste that link and use our service.

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

One of the key points of the comment you replied to is that you don’t need a very powerful model to do MCP stuff, such as local Qwen. The “let the agent figure it out” approach works much better with powerful models, such as Claude (which you mentioned you are using).

  • So MCP is useful until cheap models get better?

    • It still takes decent hardware to run local LLMs that are at all useful. What would be really cool is if we could get useful LLMs on hardware cheap enough to go into “things”.

Verging away from the topic, but I've found Claude is a great addition to HA. I want smart home features, but don't have the time/inclination to learn HA's way of working. Historically I just defaulted to Google Home because it was easier, but with Claude I barely need to touch HA configuration at all.

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.

For Home Assistant, the MCP can enable the LLM to make changes without using up excessive tokens.

For example, the only way to make a change to an HA automation via the API is to POST a whole new copy of the YAML, even if changing one things. The skill and HA MCP I use allows the LLM to use tools which make more precise changes without excessive context usage.

Certainly still works either way though. And of course your LLM instance could just roll its own tools to do the exact same thing.

That's smart! That reminds me, I have to get back into HomeAssistant. I had my whole house through it a few years ago, but the complexity and things breaking in hard to debug ways made the experience too frustrating for my wife and visiting relatives.

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.

  • Developing for HA with Claude has been great. Not only can it make all of those yaml changes based on natural language goals, but it's so easy now to create a custom dashboard or configure various apps. I was struggling with both the ChoreOps docs and its fairly cumbersome interface until I pointed Claude at it and told it what I was trying to do.

> No MCP needed

Definitely helps that the home assistant api is documented online most likely in the training data.

  • One of the nice things about MCP is that the tools have descriptions that provide guidance to the LLM. You can provide documentation in other formats like OpenAPI but its nice that the documentation is so closely coupled with MCP servers.

    • > One of the nice things about MCP is that the tools have descriptions that provide guidance to the LLM.

      It is more of a curse than a blessing. MCP pollutes agent context even when you are not using it. Use a manually invoked skill instead if you don't want to be wasting tokens on every turn and bloating up agent context making it dumber in the process.

      1 reply →