181–190 of 216 posts
- Loki
- Prometheus
- Grafana
- Incident.io
- GitHub for our codebase
- A custom MCP for our server inventory/nodes
Having all of them made it trivial for the LLM to start with an alert, search the codebase for the alert source and then review the Prom stack for additional info.
Automated a lot of the toil around digging through alerts and then making changes to fix issues.
MCPs are diminishing in value a bit, because AI Agents are getting smarter about using API/CLIs. For example, I use gh cli via Claude instead of their MCP, because I already had cli setup, so no need to use MCP. MCPs can potentially have great value if they cross multiple sources and combine results. For example at work we use an in-house MCP for log/metrics search across five different (legacy) systems. It finds cor…
gh cli prbly has a lot of training data so maybe not a fair comparison
cli tools are a natural fit for llms.
You're very likely to use those tools for other things as well, so keep the MCP as just a layer.
You can add a lot of things you wouldn't usually bother with, like telemetry, detailed logs, read only database access (you can even add a llm powered query builder on top) etc.
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A layer than honestly doesn't do much, as I understand it. What does MCP as a protocol actually solve? Is it more than a bandwagon?
Im not deep in there, but Id guess it offers some discovery mechanisms? (not sure if my understanding is correct)
Yeah had mcp in prod since late 2025. Runs 100s of tools via openrouter. I don’t get when people start banging on about ‘cli’ and ‘mcp is rubbish’. It’s damn cool and it works. And if you do some legwork it doesn’t need to pollute context so you can have 1000s of tools if required.
MCP's are great for adoption of your service outside of developer circles. Non Technical users can click a link, trigger an OAuth flow and authenticate. You can't do that with API. API still is better for developers using a AI via a CLI but MCP is easier adoption for web or desktop based clients.
This (points up)! I've read many comments about how good CLIs are, and they are right. But for developers. For non-tech people, installing the CLI is a hurdle: it involves having the right dependencies installed, controlling how you handle secrets (like API keys), and handling updates (ie. npx with a private registry). But for internal tools, once you create an MCP with OAuth, the installation (in Claude) is straight…
That's why services like https://zapier.com/mcp provide still a ton of value, because it helps non technical folks have the MCP server ready to run.
I built an MCP server for my voice assistant. By default, Home Assistant offers a few tools to the models, but I felt like it was missing some, so I built it. It has tools to get real jokes, do math, unit conversion, get stock information, search the web with Kagi, and other things I consider to be essential in a voice assistant. It even got approved by my wife. At work I use our MCP server to debug and troubleshoot…
I've been using https://github.com/homeassistant-ai/ha-mcp for my Home Assistant instance and it has been awesome.
"What amps and charging schedule should I set my EV to charge at, so that at peak electricity rate time my house battery is at 90%." Looks at my house battery, car battery, current weather forecast, and house solar production, all of which are integrated into my Home Assistant. Looks at my gmail calendar. "16 amps, 9:30am-3:30pm, higher than usual because you're driving to lunch from 11am-12pm" (shows math). It can even go ahead and set it for me but I haven't given it read/write access to my car yet.
Earlier quoted context omitted.
MCP is not just a rest api its a layer on top
A layer than honestly doesn't do much, as I understand it. What does MCP as a protocol actually solve? Is it more than a bandwagon?