Login

r/mcp

▲ 4 r/mcp+1 crossposts

Showcase: MCP App website builder

Hi there!

I am building a website builder (https://lacuno.io) which lets you connect via a MCP, so your favourite tools can edit the website instead of buying AI tokens for a premium.

But I still felt that this is hard to steer the AI to the right sections.
Now it works as a MCP App. Claude will open the editor and "see what you see".
It can see your selection, make screenshots of the app and edit anything how you like it.

This way you can just point at an element and tell it to restyle / align / reword etc.
Hope you like it!

P.S: Except some rough edges for now. I don't have any real users yet besides my wife :)

reddit.com
u/lacuno123 — 4 days ago
▲ 3 r/mcp

i got tired of re-briefing every new agent session, so i built a local memory they all share

i run a few coding agents on the same project (claude code, cursor, codex) and every new chat starts from zero. the decision, the reason, the half-finished work all disappear when the window closes, so i kept explaining it by hand.

cairntir is an MCP server that keeps that in a local database on your machine. you (or an agent you ask) save decisions, open work and outcomes word for word. new sessions get a handoff of what matters, and older stuff is searchable by meaning or by file.

no cloud, no account, no telemetry. MIT licensed. two commands to set up (python 3.11+):

pip install --upgrade cairntir then cairntir setup

site: https://cairntir.com
code: https://github.com/pnmcguire480/cairntir

been building it for a few months, new release a few weeks ago. tell me what breaks or what's missing.

u/tampa_colorao — 7 days ago
▲ 2 r/mcp

We built MCPtoAI, an open-source client for using MCP tools across AI models — looking for technical feedback

We’ve been building MCPtoAI, an open-source client for using MCP tools across different AI models without tying the workflow to a single provider.

The basic idea is:

  • install the client on macOS / Windows, or use the Linux CLI
  • add your own AI provider credentials locally
  • connect MCP servers once
  • configure individual MCP tools with Off / Ask / Allow permissions
  • switch between supported models while keeping the same conversation and MCP setup
  • use it from Desktop, the web, or a phone while tool execution remains controlled by the paired device

One of the main things we wanted to avoid was giving a remote AI session unrestricted access to local capabilities. Provider credentials, MCP OAuth tokens and permission settings stay on the device, and higher-impact actions still require explicit approval.

The client side is open source:

GitHub: https://github.com/mcptoai/MCPtoAI
Demo: https://youtu.be/nAhHaHcHs1U
Website: https://mcptoai.com/

We’re at the point where feedback from people who actively use MCP is more useful than continuing to polish things in isolation.

We’d especially like feedback on:

  • whether the per-tool permission model makes sense
  • how the local stdio vs remote MCP handling feels
  • the device / relay architecture
  • model switching while keeping the same MCP setup
  • anything in the MCP workflow that feels unnecessarily complicated

This is obviously our own project, so this is self-promotion, but the main goal of posting here is to get technical criticism and find what’s missing before we push it more broadly.

u/abktya — 7 days ago
▲ 1 r/mcp

How are you monetizing proprietary data through MCP?

Hi everyone,

I've been working quite a bit with MCP over the last months, and one question keeps coming back:

If you own a valuable dataset or paid API and expose it through MCP, how do you actually get paid when an agent uses it?

Today it usually still looks like this:

create account → choose a plan → add payment method → get API key → then the agent can call the API.

What I’m interested in is a different model:

An agent discovers a data product, sees that one call costs for example €0.25, has an approved budget, buys that single call and gets the result.

No separate subscription for every provider.

Full transparency: I’m currently building and testing in this space, so I’m trying to understand the provider side before making too many assumptions.

If you already sell data or API access:

What would stop you from trying this tomorrow?

Payment?
Authentication?
Licensing?
Accounting?
Trusting an agent with a budget?
Or simply no real customer demand yet?

reddit.com
u/ValosSantanos — 7 days ago
▲ 4 r/mcp

I built a Jev-based wingman for browser MCP servers: it works alongside Playwright MCP, takes over the clicking, and hands back what it can't do (34/34 runs, 30% cheaper)

AI agents drive browsers one click at a time, and every click costs a full model turn. I built jev-browser-wingman to hand those clicks to TypeSafe's Jev, then benchmarked it against Claude Sonnet 5.5 doing its own clicking.

It is a wingman, not a replacement. Your browsing server (Playwright MCP in my tests) stays installed, and the agent keeps its tools for reading the page, tabs, dialogs and dragging. Wingman takes over only the clicking and typing: the agent sends all the steps of a task in one call, Jev picks the right element for each step, and wingman clicks and checks the page.

It knows its limits. When Jev isn't sure, or a step needs something wingman doesn't do (a dialog, a drag, content inside an iframe), it hands that step back to the agent instead of guessing.

Full write-up: https://hrishikesh917277.substack.com/p/handing-an-agents-browser-clicks

Repo: https://github.com/coderexpert123/jev-browser-wingman. I am not affiliated with TypeSafe.

u/Hrishikesh90 — 7 days ago
▲ 1 r/mcp

When people say “MCP is bad at X,” are we talking about the same problem?

Disclosure:I work at MCPJam, so that’s where I’m coming from.

While building evals, I’ve been thinking about how often MCP vs CLI discussions lump a few different problems together.

An agent picking the wrong tool, struggling to pass data between tools, and filling up its context window can all look like “MCP isn’t working.” But fixing one won’t necessarily fix the others.

Passing data between tools: Can the agent take the output from tool A and use it in tool B? If the output is prose, it may have to extract the values first. Structured output can help, though the next tool still needs to accept that data.

Context getting crowded: Tool definitions and results take up space, even when every tool is clearly described. Our evals don’t measure context size, so I don’t have results to share on that.

Picking the right tool: This is what we’ve been focusing on with evals.

Take a notes server with two tools:

  • find_notes filters by tag.
  • search_notes searches the text of your notes.

“Find my notes tagged travel” should use find_notes. But an eval that only checks whether it called find_notes would also pass if it called search_notes too, for no reason.

So we check both: did it call the expected tool, and did it avoid the other one? Then flip the test with “Which notes mention passport?” and run both cases several times to see how consistent the choices are.

That tests tool selection. It doesn’t tell us whether the agent can reliably chain several calls together, or whether code orchestration would work better. Same with checking a tool’s arguments or output: that tells you one step worked, not that the whole workflow did.

When you’ve had trouble with MCP, what went wrong? Wrong tool, trouble using the results, too much context, or something else?

reddit.com
u/Paoli99 — 7 days ago
▲ 4 r/mcp

I built APIBlaze to handle OAuth + AuthZ for MCP servers

Hi Everybody,

I've been helping build https://apiblaze.com, a serverless MCP/API gateway that handles a lot of the stuff you need around an MCP server.

What we noticed was that there are a ton of MCP servers, but getting from “my business logic works” to “I can safely publish it on the internet” is a different problem. Once you actually want to expose it, you still have to deal with things like OAuth, AuthZ, rate limiting, etc.

APIBlaze handles that stuff at the gateway. It has OAuth built in and lets you define authorization policies using plain English sentences like “only the person who created a record or an admin can read or change it” that are enforced at the gateway, instead of having to build all of that authorization logic into your backend.

One thing we really wanted to make easy was local development. APIBlaze can host the MCP server and OAuth/login flow while forwarding requests to your backend, even if your backend is running on localhost. So you can connect Claude/ChatGPT to it, authenticate, and make changes to your backend while testing it locally.

If you want to check it out or run it, getting started is pretty easy:

Enter this in your terminal:

npx apiblaze create --target https://ninopizzas.com/openapi.yaml

OR

Ask your LLM, such as Claude or ChatGPT:

Show me what APIBlaze does using npx apiblaze skills

You can also use it with an existing API/backend rather than building everything specifically for MCP.

It's still in beta, so I'd love any feedback. I'll try to respond to questions as fast as possible, so fire away 😄

u/Ok_Direction_3846 — 7 days ago
▲ 10 r/mcp

I built a self-hosted Gmail MCP for multiple accounts in Claude and Codex

I'm the maintainer. I built this to use my personal and work Gmail accounts from Claude and Codex while choosing the mailbox explicitly for every operation.

Repo: https://github.com/alexneamtu/gmail-mcp (MIT)

It exposes one Streamable HTTP endpoint with:

  • Account aliases such as personal and work, required on every tool.
  • Gmail search, message reading, label lookup, and plain-text draft creation.
  • Optional sending of existing drafts and applying/removing labels.
  • Owner-only Google login, OAuth with PKCE, and encrypted credential storage.

You host your own instance and use your own Google OAuth project. The documented setup uses Node 24, Linux/systemd, and Cloudflare Tunnel for HTTPS. Mailbox enrollment uses a browser plus SSH forwarding when the server is headless. The README covers Claude and Codex setup, re-authentication, revocation, updates, and rollback.

A couple of limits: Google's compose scope includes sending permission even though drafts mode omits the send tool. In full mode, approval to send is handled by your assistant client; there isn't a separate server-side approval screen for each email.

This is an early release that I'm running for my own accounts. I'd appreciate feedback on the installation process, especially from people connecting accounts across different Workspace domains.

u/CodeCoffeeCocktails — 7 days ago
▲ 3 r/mcp

rhp-mcp: make beautiful infographic/editorial style charts using rhp 2.0.

I just released rhp 2.0 around 2 weeks ago. rhp is an open-source html/CSS-type charting library I have been working on for 3 years. I finally got it to a good place in performance and capability to warrant pushing it out. Unfortunately, the library is a SolidJS library atm and plans to make it framework agnostic are going to take awhile. Meanwhile, I created an mcp server and a skill that guides AI agents to properly use rhp and produce something usable from just a single short prompt.

I just released version 1.01 of the mcp server: https://www.npmjs.com/package/@bezda/rhp-mcp

All the recipes in the rhp gallery were generated using the skill or mcp server.

u/bezdazen — 6 days ago
▲ 5 r/mcp

An MCP tool on your allowlist has no call budget. One agent loop and it runs until something else stops it

An allowlist decides one thing: whether an MCP tool is allowed to run. It does not count how many times that tool runs, and it does not read the arguments the model fills in. So an approved tool is approved for every call, including the ones you were not thinking about when you added it.

An agent in a retry or planning loop calls a deploy or a delete_rows tool in production. The name is on the allowlist, so call two, call five, call twenty all pass the same check and go through. The allowlist was never counting.

The arguments are the other half. A name check approves delete_rows, but the model writes the arguments, and that is where a drop table or a where 1=1 shows up. The allowlist never reads that far.

This is the same gap behind the recent Figma client-name allowlist pushback: a name is a label the caller reports about itself, and a label does not limit what the caller does next.

We run a gateway in front of the tool calls. Every call gets checked against the allow and deny lists and a per-tool rate limit, the arguments get scanned on each one, and a single request can only fire so many calls before the gateway stops it.

What are you using to cap this today: a per-tool rate limit, a hard call budget per turn, human approval on writes, or nothing yet?

reddit.com
u/Future_AGI — 7 days ago
▲ 2 r/mcp+1 crossposts

I made RelayDesk, an MCP bridge from Claude and ChatGPT Work Mode to a computer you control

Disclosure: I’m building RelayDesk.

I built it to cut out the copy/paste loop between an AI assistant and the machine where the work needs to happen. RelayDesk connects MCP-capable assistants to a computer, server, or VM you control, runs a command, and returns the real output.

Claude connects through MCP. ChatGPT currently works with RelayDesk only in ChatGPT Work Mode; it does not work inside regular ChatGPT chats. RelayDesk is early, and the permission boundary around reading logs, writing files, or restarting services is the part I most want feedback on.

I’m looking for people willing to try it on a spare machine or VM and tell me what they would want to approve before giving an agent access.

https://getrelaydesk.space

What should the first permission prompt show?

u/whateverxp — 6 days ago
▲ 3 r/mcp+1 crossposts

I built an MCP server that lets Claude publish the tools it builds and share them with your team

Claude Code is great at building small tools, but they usually stay stuck on localhost.

ShareBox is a self-hosted platform plus an MCP server. You ask "build a vacation tracker for my team and publish it on ShareBox": Claude reads the built-in guide (`sharebox_guide`), writes the tool, calls `sharebox_publish` and replies with an HTTPS link. Then "share it with anna@company.com" → `sharebox_share`, effective immediately.

The platform handles Google sign-in, per-tool storage and sandboxing, so the tool Claude writes never needs its own login or database: it just calls `sharebox.me()` and `sharebox.collection("vacations").add(...)`.

Setup:
npm i -g sharebox-cli
sharebox login your-instance.example.com
claude mcp add --scope user sharebox -- sharebox mcp

It's also in the official MCP registry as io.github.zalaso/sharebox.

Fully built with Claude Code itself. Self-hosted, AGPL: https://github.com/zalaso/sharebox

u/Zalaso — 7 days ago
▲ 2 r/mcp

MCP server for Adobe After Effects (47 tools) Corps :Built an MCP server that let Claude read and edit After Effects projects directly

I just Built an MCP server that let Claude read and edit After Effects projects directly: layers, keyframes, expressions, compositions, audio analysis, style memory (save a look, reapply it elsewhere), and a read-only project audit before delivery etc...

It runs through a panel inside AE that relays commands over a cloud bridge, so it works with claude.ai without a local setup.

The goal is to help the motion designers and studio to gain time on their project.

Free tier: 8 calls/month after a 7-day trial.

Lmk what you think and if you have questions about it do not hesitate

works or else.

neykofx.com/mcp PS: if you go on the website and you don't understand the demo of the tool it's because it's in french.

reddit.com
u/Less-Slip-9964 — 7 days ago
▲ 4 r/mcp+1 crossposts

Submitted to Claude’s connector directory or ChatGPT’s app directory? How long did review take?

I work at MCPJam, and we’re preparing our own submissions to Claude’s connector directory and ChatGPT’s app directory. I’d like to hear from developers who’ve already gone through review or are still waiting.

I’m interested in both the timeline and what happened during the review itself. How long did it take to get an initial response? Was that an approval, a request for changes, or just confirmation that your submission was being reviewed?

A few things I’d appreciate hearing about:

  • Which directory did you submit to, and roughly when?
  • If you’re still waiting, have you received any updates since submitting?
  • If you were asked for changes or rejected, what feedback did you get? Was it specific enough to know what to fix?
  • If you resubmitted, how long did the next round take?

Also, looking back, was there anything you wish you’d tested or documented before submitting? I’m especially curious about things that worked in your own testing but came up during review.

Experiences with either directory are appreciated!

reddit.com
u/Paoli99 — 14 days ago
▲ 2 r/mcp+1 crossposts

MyA11yReport-MCP, accessibility tools and skills for your AI agent

Hello everyone, I am Charles, a web developer interested and constently learning about accessibility. I built this MCP server to help myself and other devs using coding agents build more accessible websites and web apps. The MCP spins a chrome session locally, and gives the agent the following tools

  • Page interactivity (click, type, check, navigate, etc)
  • Run an automated scan using axe-core
  • Page structure tools (Tab order, structure, images with alt/decorative states)
  • Contrast checker with failing states for small, large texts for WCAG 2.1 AA, AAA
  • An audit template skill for assisting you in audits

MCP: https://www.npmjs.com/package/mya11yreport-mcp
Repo: https://github.com/mya11yreport/mya11yreport-mcp

Give it a try and let me know if you have questions or ideas on how it could help you!

Disclaimer: I am building an accessibility monitoring platform and the README mentions it, but the MCP works without the platform. That's why I put the Brand Affiliate tag.

reddit.com
u/CharlesLoubao1 — 12 days ago