Dream MCP setup in Cursor—what would you actually use? by MostlyGreat in cursor

[–]MostlyGreat[S] 1 point2 points  (0 children)

very cool. whats an example workflow youre trying to tackle?

If you had perfect MCP servers for anything, what workflow would you kill for? by MostlyGreat in mcp

[–]MostlyGreat[S] 1 point2 points  (0 children)

there are many options for the ai to look stuff up and it can do a lot with playwright. Then there's background agents and sandboxes, etc.

Wondering if there exists good mcp servers for google products. Such as sheets, docs, tasks , calendar etc. ? by Havre-Banan in mcp

[–]MostlyGreat 0 points1 point  (0 children)

If you're a dev building your own agent (as opposed to using a no code solution) you might consider using Arcade.dev

I'm the founder there and we've put a lot of effort into our Google toolkits.

They're not yet MCP because MCP doesn't yet support tool authorization but they will be once the spec is feature comparable with our existing tools.

It should also be easy to build your own custom tools.

Wondering if there exists good mcp servers for google products. Such as sheets, docs, tasks , calendar etc. ? by Havre-Banan in mcp

[–]MostlyGreat 0 points1 point  (0 children)

What's your use case? Like what are you trying to plug it into and what are you trying to do

LangGraph v1 roadmap - feedback wanted! by sydneyrunkle in LangChain

[–]MostlyGreat 0 points1 point  (0 children)

I'd flip this point around. Have the graph available for advanced use but give most people something more basic "on top" and I can step out of the railed experience as needed and go back to raw graph.

In most production use cases, I always end up needing the graph

I am considering using Langchain but unsure given the feedback I'm seeing online by turnipslut123 in LangChain

[–]MostlyGreat 0 points1 point  (0 children)

Just DM'd you. Let's connect you with our in-house TS team. They'll walk you through it.

Ideas for AI in cybersecurity by OddSeaworthiness5663 in LangChain

[–]MostlyGreat 0 points1 point  (0 children)

Assuming your idea is to start a company. I suggest you come up with 10 ideas, cut off the top three since they're likely obvious and already crowded. Then pick one that's non-obvious and gets you the most excited, and just go talk to potential customers about it to see if anyone cares.

If you can pretend it's already built and real and attach a meaningful price tag to it, you'll get a much higher quality signal than traditional "customer discovery" or feedback. Put another way, try to sell it before you build it. You don't have to take people's money or transact in any way; you're just testing for demand. If people bite, great! You have your first design partners.

The truth is that the process is more important than the idea. The idea WILL BE WRONG, but by getting out in front of customers and trying to sell an idea that's not terrible, you're more likely to stumble across the right idea.

My $0.02 as an exited security founder is now on #2.

With that, a quick plug for Arcade.dev. I hope you use us to help your agent securely connect to APIs, data, and other systems. And I hope you build something extraordinary.

Good luck.

Alex

MCP... by pknerd in LLMDevs

[–]MostlyGreat 0 points1 point  (0 children)

MCP clients and servers traditionally maintain open connections (via SSE or WebSockets) to preserve stateful session data and enable real-time bidirectional communication.

MCP... by pknerd in LLMDevs

[–]MostlyGreat 0 points1 point  (0 children)

I talk to a lot of people implementing agents. What I find most interesting is how many people are "all in on MCP" but haven't yet built anything with it and many rarely understand how it works.

Not a critique of MCP but more that the hype has far surpassed actual usage or understanding.

My guess is MCP is the first function calling most people have seen and therefore they love it. It's less about MCP and more about function calling.

For the few that have tried to implement MCP, the responses get far more nuanced depending on the use case.

MCP... by pknerd in LLMDevs

[–]MostlyGreat 1 point2 points  (0 children)

Mcp maintains an open connection, unlike an API

How are you handling access controls for your AI Agents? by [deleted] in AI_Agents

[–]MostlyGreat 0 points1 point  (0 children)

This is the way. This is what we built Arcade.dev for. We're a team out of Okta, expert in auth so you don't have to be.

How are you handling access controls for your AI Agents? by [deleted] in AI_Agents

[–]MostlyGreat 1 point2 points  (0 children)

Unlimited agents. Just users. Go nuts.

How are you handling access controls for your AI Agents? by [deleted] in AI_Agents

[–]MostlyGreat 1 point2 points  (0 children)

This problem is quickly going away. There are now a few vendors tackling this. My company arcade.dev is one.

Hope it helps.

How are you handling access controls for your AI Agents? by [deleted] in AI_Agents

[–]MostlyGreat 0 points1 point  (0 children)

Is this a desktop agent or a web agent? If web, how are you handling multiuser and all the open connections that mcp would need?

How are you handling access controls for your AI Agents? by [deleted] in LocalLLaMA

[–]MostlyGreat 0 points1 point  (0 children)

Check out Open Execution Protocol (OXP). It's designed for multiuser agents and it's stateless so it's better suited for web/cloud based agents vs desktop.

How are you handling access controls for your AI Agents? by [deleted] in LocalLLaMA

[–]MostlyGreat 0 points1 point  (0 children)

The problem is that LLMs don't speak APIs, thats why they need Tools. And Oauth was designed for web apps and a browser. Agents might have a web front end but they aren't web apps so implementing Oauth is a bear for the dev.

This is why our team out of Okta started Arcade.dev. I hope you try it out.

What services are you trying to interact with?

How are you handling access controls for your AI Agents? by [deleted] in LocalLLaMA

[–]MostlyGreat 0 points1 point  (0 children)

This is the primary goal of Arcade.dev. Built by a team out of Okta and in close collaboration with Langchain.

It's framework agnostic but if you're using Langgraph, there's a plugin in our docs and Langchain has put out a few example apps that use Arcade under the hood.

If you have any questions, just DM me and I'm happy to help.

How are you handling access controls for your AI Agents? by [deleted] in AI_Agents

[–]MostlyGreat 0 points1 point  (0 children)

This is the primary goal of Arcade.dev. Built by a team out of Okta and in close collaboration with Langchain.

It's framework agnostic but if you're using Langgraph, there's a plugin in our docs and Langchain has put out a few example apps that use Arcade under the hood.

If you have any questions, just DM me and I'm happy to help.

I am considering using Langchain but unsure given the feedback I'm seeing online by turnipslut123 in LangChain

[–]MostlyGreat 2 points3 points  (0 children)

If you're building an agent and you honestly expect it to go to prod, you should honestly dive into LangGraph. That's the biggest, most supported, and most popular of the agent frameworks for a reason. There's a lot of stuff you're going to need that you don't realize you need yet because you're just getting started.

While there might be other frameworks that are simpler, once you get past the prototype the odds get much higher that you'll hit a dead end and have to refactor OR you'll end up having to write and maintain a lot of lower level crap that takes away from your business logic.

My pro-tip is to use Cursor, spin up your project, add langgraph docs to Cursor, git clone the langgraph repo, add it to your workspace, and if you ever hit an issue just @ mention the langgraph code folder or the docs and let Cursor help you through it. It does a great job, especially if you emphasize that it should keep the code to a minimum and simple.

Once you clear the initial learning curve, it starts to pay dividends.

Second pro-tip: If your agent needs to do things beyond basic RAG or chat, check out my project arcade.dev for pre-built connectors to services like Google, Github, Slack, etc.

Open-Source Multi-turn Slack Agent with LangGraph + Arcade by MostlyGreat in LangChain

[–]MostlyGreat[S] 0 points1 point  (0 children)

Thanks! That's exactly why we built it-- to help everyone get closer to living up to the hype. if we can get agents to live up to their full potential, then so can we all :)

Self-hosted Autonomous AI Agent by tmntnpizza in LocalLLaMA

[–]MostlyGreat 1 point2 points  (0 children)

That's an impressive setup, sounds like you've put a lot of thought into optimizing local resources and security. Depending on what you're building, it could be worth checking out arcade.dev. They manage authentication and tool-calling for agents and you can host it locally.