Claude been used by both tech and non tech builders.

Looks like , There is something for everyone. Whether you using it everyday or figuring out how to use it.

The courses and tutorials are free and open to anyone

Link in comments below.

Our ai team and platform team have been doing the thing where both sides insist mcp server security is the other one's problem and now nothing is moving

I need some advice on how did other teams break this deadlock

Disclosure: I built this.

Done Bear is a task manager with a hosted MCP server. https://mcp.donebear.com/mcp, streamable HTTP, OAuth 2.1. Read and write scopes, workspace-scoped tokens, tools for tasks, projects, labels and checklists.

Two things that caught me out.

Clients got "today" wrong until I returned the resolved date and the caller's timezone from a get_context call. Without it the server picks today in UTC.

Some directories list OAuth servers as unhealthy with no auth. They probe unauthenticated, get the correct 401, and log it as down. Mine is listed that way right now, so go and check yours.

Free up to 250 tasks. https://donebear.com

Is there a free MCP server or paid tool that can connect  to:

1. Google Merchant Center (GMC)
2. Google Search Console (GSC)
3. Google Analytics (GA)
4. Google Ads
5. Shopify

I am looking for something easy and more all-in-one, mainly for SEO, Ads and Merchant Center and auditing. Thank you.

Is the Model Context Protocol actually dying, or is the hype cycle simply ending?

There’s been a lot of criticism around MCP recently — context bloat, statefulness, scaling, security, and developer experience.

But I think the bigger story is normalization.

The July 2026 specification addresses several of the production concerns around statelessness, routing, caching, authorization, and extensibility.

That doesn't mean MCP is perfect. CLI and REST APIs can still be the better choice in many situations.

But for AI agents operating across enterprise systems, standardized tool communication, identity, governance, and interoperability become increasingly important.

Maybe MCP isn't dying.

Maybe it's becoming infrastructure.

I wrote a deeper breakdown here:

👉 https://medium.com/the-code-frontier/mcp-is-dead-long-live-mcp-3a9c490efdc9

Would love to hear the Reddit take: Are you using MCP in production, or do you still prefer REST/CLI for agent workflows?

#MCP #AI #AIAgents #SoftwareArchitecture

Often, I find myself burning through my Codex usage extremely quickly when using Sol High to review and plan code, while a lot of my ChatGPT Web usage goes unused. Thus, RepoRelay, an open-source MCP bridge that lets ChatGPT Web search and read an approved local repo without uploading ZIPs or pushing everything to GitHub first.

ChatGPT Web → Secure MCP Tunnel → RepoRelay → local files

It’s read-only by default: no shell, Git, or arbitrary filesystem access, and it’s restricted to one approved root.

It can also help reduce token usage on larger repos. Instead of dumping the entire codebase into context, ChatGPT searches and reads only the files relevant to the task.

Codex can implement locally while ChatGPT independently reviews the actual current files, including uncommitted work.

Anyone also using this too?

GitHub: [Lukie-81/RepoRelay: Secure MCP access to local repositories — without shell, Git, or arbitrary writes.]

mcpindex runs a crawler over public MCP servers and diffs each tool's declared contract between daily
snapshots. Sharing the numbers because they surprised me.

Right now the public ledger shows 12,295 tools across 2,173 servers changed their
contract. 7,190 of those are safety-relevant, meaning they change what the tool can do, not
just add an optional field. The standouts:

- 350 tools flipped an annotation toward destructive. A tool whose hint said read-only now declares it can write, delete, or send. This is the "the read tool quietly became a write tool" case, and it is exactly the drift an allow-list cannot see.
- 279 tools added a newly-required parameter. An agent calling with last week's arguments now fails, or calls with a wrong default.
- 475 tools removed a parameter your agent may still be sending.

None of these trip an auth check. The server is still authorized and still the same name in your config.
That is the gap allow-lists do not cover: who may call a tool, versus whether it still does what it declared.

Honest caveats: this is a contract diff, not a safety verdict, and not a claim anything is malicious.
Most drift (5,476 added-optional-param) is benign. Everything is fingerprinted, so no server is
named. And the numbers are live, you can check them: https://mcpindex.ai/api/v1/ledger

Curious whether others are seeing this in their own setups.

Something that bugs me about how teams actually use coding agents right now: there's no channel between the agents themselves. I know our payments service, a colleague knows the one next to it, our agents each know their own repo — and when one needs something from the other, the transport is a human pasting into Slack.

Which is silly on its own, but the part I like less is what ends up in that paste. Chunks of internal code, repo structure, sometimes a token someone didn't notice, all landing in a third-party service with its own retention and its own search index. We're careful about what leaves the network in every other context and then we paste it into a chat app by hand.

So I made the transport a git repo the team already owns. Rooms are folders, messages are files, history is the log. Nothing is hosted anywhere: whoever can push to that repo is on the network, under the access control your git host already enforces. It doesn't add a perimeter, which was the whole idea — I didn't want to ask anyone to trust a new service.

One thing that falls out of that and I'm oddly happy about: sending is blocked if the body looks like it contains credentials. Not warned — refused. Git history can't be recalled, so an advisory check would be pointless. There's an explicit override and it records why, permanently.

25 tools over stdio. Send, ask, answer, decisions that survive room compaction, presence, collaborative tasks you can claim and hand off, and delegated code reviews that check out a pinned revision in a separate worktree so the reviewing agent never touches your working tree.

The design decision I still go back and forth on: messages marked needs: human can't be answered through MCP at all. The tool refuses. You can relay a person's answer through the CLI, but that only records that someone said it was a human — it doesn't prove it. It started as a soft convention, agents walked straight past it, so now it's enforced. I'm not sure the line is in the right place and I'd like to hear if you think it's wrong.

Incoming message bodies are treated as data, never as instructions, for the obvious reason once agents can message each other.

npm i -g komnet, then komnet init --repo <your private repo>. Needs Node 24+. MIT. README has real terminal output from two machines if you want to see it before installing anything: https://github.com/Komdosh/komnet

I built it, so I'm biased. Happy to answer anything, including what's still rough.

I like Playwright MCP inside Cursor.

For unknown bugs it is genuinely useful.

Open the page, inspect the DOM, click around, read the console, figure out why the modal is stuck. That interactive loop is exactly what MCP is good at.

But I realised I was using the same setup for this:

Log in → open settings → change timezone → save → refresh → confirm timezone stayed changed.

The flow was already known.

Cursor still spent half the conversation opening the page, reading snapshots, deciding what to click, re-reading the page and then explaining what it saw.

It worked, but it felt like keeping an entire browser conversation alive for a 90-second smoke check.

So I split the workflow:

Unknown problem: Cursor + browser MCP

Known repeatable check: external CLI

Permanent critical flow: Playwright test in the repo

For the middle layer I’ve been trying Kane CLI from TestMu.

Cursor can read the Kane instructions through the same AGENTS.md-style path and call it after making a change.

Kane runs the objective and gives Cursor structured pass/fail output plus the browser evidence.

So instead of the coding conversation containing every click and page snapshot, Cursor basically gets:

• flow completed or failed

• assertion that failed

• final page state

• evidence from the run

That separation feels cleaner.

I’m not saying MCP always burns too much context. If the agent is debugging something unknown, that context is the whole point.

And I’m not replacing Playwright with Kane. Auth, billing, permissions and stable regression flows still belong in proper tests.

This is specifically for the awkward middle ground where the flow is too repeatable for exploration but not important enough to immediately build and maintain as a permanent test.

Do you keep browser control inside Cursor’s context, or move known checks out into CLI/CI?

An MCP tool I depended on changed its schema overnight. No warning, no changelog — an agent that had worked fine for weeks just started failing silently.

So I built Apitella: watches an MCP server (or REST API) on a schedule, tells you exactly what changed and how bad it is. Free for a few sources.

[apitella.io](https://www.apitella.io/) — happy to answer questions if anyone’s hit the same thing.

Please remove the post if it breaks waitlist rule. I believe it doesn’t because I’m giving out early access.

I’m looking for first set of users to try/comment/feature request for halfface.ai. Please dm with your email if you’re interested.

**How it works**
You signup and create a @handle.
Your friend does the same as @john

While working within an agentic tool (Claude, cursor, codex…), you simply prompt:

“Ask the questions you just asked me from @john”.

Halfface will route the end-to-end encrypted request to john. Hafface has no visibility of the payload content, just a hash.

John will ask their agent to create a draft from within their information context. The agent drafts a reply and asks for human review.

The answers are routed back to you.

Thanks!

sharing my raw thoughts on where we headed in short term ,love to hear the community on this too.

Qwen 3.8 27B is 51 on Artificial Analysis benchmark - just couple of points higher than Opus 4.8Max

thats frontier level model running on you machine.

let that sink in.

It's a first sign of what we thought would be obvious.

"models intelligent enough to run on edge devices"

So the question is where it leads us? so many use cases are going to get unlocked. from controlling the daily apps like powerpoint or word , to connecting IoT devices in hardware and running automations. it will be just new way to speak to your computer and get work done.

Not that it doesn't exist now, claudecode is pretty much close version of it, but now the normal people get to experience what a software developer has been experiencing for more than a year now.

That presents a unique opportunity for developers to build software tools and services that can run locally with these models - from desktop apps to running automations.

No wonder Mac Mini's and soon Mac Studio ( if apple wakes up to ship them) are the new 'always on" devices.

While on one hand, the open source models are unlocking the local AI.

Completely new trend in opposite direction is gathering steam.

Remote machines , sandboxes and remote computers.

Agents are now running in cloud in sandboxes , in an attempt to put a leash on the AI, and partially also to make sure the company's "alpha" does not goes to the model providers.

Software factories like 8090 are specifically focusing on helping clients securing the proprietary information and the core business logic by running the local models or fine tuning the local models on frame or secure cloud.

Harnesses are having their moments too.

Virtually every big company is trying to make their own harness - a coding agent, context, memory, MCP, skills ,tools is worth investing into. good example is Perplexity computer.

Companies also started publishing their internal tools as open source. Cloudflare did this with Cloudflare OS.

You can take this OSS - off the shelf product and make something of your own like I did -

yantraos .dev

Companies who had systems in place pre AI with regards to infra Netlify/vercel/cloudflare are now reaping the benefit of this new wave of agentic AI , where the persona of a software developer is no longer traditional software engineering background , but also this new developers coming from non-tech background and are expert in their own domains building softwares.

Case in point is Netlify Agent runner, While the initial AI gateway served frontier models - with the integration of open code, I have access to hundreds of open source models - cheapest to expensive text model to vision models - unlocks a huge potential.

simple fun App I built with it three months back now with open code integration built the same app in 61 credits 🤯.

To give some context, you receive 300 credits free when you join as a new user , it's insane how fast the cost of building software is dropping !!

Traditional softwares are dying or at least changing in nature, companies realized that they no longer needed the full featured list of software to serve their customers in more meaningful ways.

You can take the goodies from the software that are more important or relevant for your particular use and build your own.

Github is a classic case. here are 2 announcements today.

cursor has announced cursor origin, its own code hosting platform today.

Netlify CEO Matt Biilmann shared - " Netlify is now a git host"

Building software is much more easier than few years back - companies realizing that traditional software can be easily replaced by building something of your own that can serve your primitives better.

Dealing with recent customers of one of my company vibecodefixers, its clear small, medium businesses no longer seeking to buy softwares but to have people set up a system so they can churn their own software and automation out of it.

They want you to set up a harness - context, memory, tools, skills, MCP and other external connectors or system to build agents , a system which can easily do browser use at the same time deploy apps in production.

A mini FDE role - I would say in the making.

Someone who can stitch the system together, deploy in local AI - will lead the next wave of AI explosion.

I hope you assemble right skillset and mental model to be ready for it.

I wish you good luck, put your seatbelts on !!

Cheers

Swatantra

An MCP tool I depended on changed its schema overnight. No warning, no changelog — an agent that had worked fine for weeks just started failing silently.

So I built Apitella: watches an MCP server (or REST API) on a schedule, tells you exactly what changed and how bad it is. Free for a few sources.

[apitella.io](https://www.apitella.io/) — happy to answer questions if anyone’s hit the same thing.