r/modelcontextprotocol

I wanted an agent that reads Granola meeting notes, checks Linear, and posts the next action in Slack.

Instead of clicking through a dashboard, I described that job in Claude Code. Runbear MCP returned a proposed agent setup. I reviewed the changes, approved the write steps, and tested the result in Slack.

I work on Runbear, which built the MCP in the 18-second clip.

What felt different here is that MCP was not just giving an existing agent another tool. It became the interface for configuring the agent itself.

That made me wonder how much of an agent platform's dashboard MCP should replace. Basic setup and deployment worked through MCP; advanced settings and knowledge-base sync still stayed in the UI. Where would you draw the line?

I've been messing with on-device AI stuff for Apple Silicon Macs and put together LocalLM Lab to make experimentation easier.

It started as a simple prompt interface as just a way to poke at Apple's on-device foundation model and see how it responds. Since then I've added an OpenAI API-compatible endpoint (localhost or external IP), so you can point existing tools/scripts at it like any other local model server.

Right now it's built on Apple's Foundation Models framework. With the new LanguageModel protocol Apple introduced this year, the framework isn't locked to Apple's on-device model anymore. Any provider that ships a conforming Swift package (local MLX models, Claude, Gemini, etc) should be a plug-in. I'm looking at wiring that up so LocalLM Lab isn't limited to just the built-in model.

It's a free download from thisbrain.ai/locallm

Let me know how you think LocalLM Lab should evolve. MCP? Model switching in the UI? Something else?

i’m the author of adport. this is a real session against my own apple ads account using the new v1 api. claude creates the campaign, ad groups, and keywords through mcp. everything starts paused, and every write needs a preview plus a second approval before it reaches apple.

i built it because ad automation from agents needs stricter safety than a normal api wrapper. i’d value feedback from people who actually run apple ads.

install: npm install -g adport

source: https://github.com/ynnickw/adport

Most agents today are already pretty powerful and requires minimum prompt engineering, and the app builder's value was in the easy set up. So I made an MCP that does what lovable/replit do, but uses your AI subscription's tokens instead. It ends up being a 60+ tool MCP but it's been working pretty well. It does require a good model (opus or terra) to work well, but overall it's been able to do a pretty good job.

Check it out here: https://floot.com

And let me know if you have any feedbacks!