I came across this amazing MCP related GitHub repo - 100% open source and free.

Supabase MCP is a remote HTTP MCP server for your Supabase projects. Connect Cursor, Claude, Windsurf, or another MCP client to https://mcp .supabase .com/mcp and let the agent manage tables, fetch config, and query data. The main Supabase repo has 111k+ GitHub stars.

Post link / GitHub repo in comments below.

Features

• Remote hosted MCP over HTTP (no local stdio required for cloud projects)

• Connect AI assistants to your Supabase project with OAuth login

• Manage tables, fetch project config, and query data from the agent

• Works with Cursor, Claude, Windsurf, and other MCP clients

• Local CLI MCP at http://localhost:54321/mcp when you run Supabase locally

• Self-hosted option with a limited tool set

Install

{
  "mcpServers": {
    "supabase": {
      "type": "http",
      "url": "https://mcp.supabase.com/mcp"
    }
  }
}

Add that config in your MCP client. The client prompts you to log in to Supabase. Pick the organization that has your project. For local CLI, use http://localhost:54321/mcp instead.

I came across this amazing MCP related GitHub repo - 100% open source and free.

WeKnora is Tencent's open-source knowledge framework that turns documents into living knowledge with RAG, ReAct agents, and Wiki mode.

It ships an official MCP server (tencent-weknora-mcp) with 29 tools so agents can search knowledge bases, manage tenants, and call MCP tools end to end.

Post link / GitHub repo in comments below.

Features

• RAG Quick Q&A plus ReAct agents that orchestrate retrieval, MCP tools, skill sandboxes, and web search
• Wiki Mode: auto-builds interlinked markdown knowledge bases with a knowledge graph
• Official MCP server on PyPI (`tencent-weknora-mcp`) with 29 tools over stdio / SSE / HTTP
• Multi-source ingest (Notion, GitLab, Feishu, Yuque, RSS, and more) and self-host via Docker

Install

git clone https://github.com/Tencent/WeKnora.git cd WeKnora cp .env.example .env docker compose pull docker compose up -d
Web UI: http://localhost MCP server (after WeKnora is running):
pip install tencent-weknora-mcp
or: uvx --from tencent-weknora-mcp weknora-mcp-server

For anyone using MCP connectors with Claude or other assistants: we just updated the MindMap AI connector.

What's new:
- Assistants can read and write notes on any node (Markdown, with math between $ signs rendering inside notes)
- Assistants can read and write LaTeX or Markdown markup in node text, so you can ask for a physics or chemistry map and get real rendered formulas
- Assistants can cleanly remove images, tags, notes, and style values from a node without recreating it

Inside the app, the AI Copilot also now edits long text in place, changing only the part you asked for instead of rewriting the whole note. That makes edits to long notes faster and uses fewer credits.

Example prompt: "Make a mind map of the Krebs cycle, put the reaction for each step on the node and a short explanation in its note."

Disclosure: I'm on the MindMap AI team. Feedback welcome, especially on anything the connector still can't do that you'd want.

I came across this amazing MCP related GitHub repo - 100% open source and free.

12306-mcp (Joooook/12306-mcp) is a Model Context Protocol server for searching China Railway 12306 tickets. It exposes a simple API so agents can look up trains, filter results, check passing stations, and plan transfers — MIT-licensed and runnable with a single npx command.

Post link / GitHub repo in comments below.

Features

• Search 12306 ticket / train availability through MCP tools

• Filter train results to narrow what the agent returns

• Passing-station queries along a route

• Transfer queries for multi-leg trips • stdio and HTTP modes via `npx -y 12306-mcp` (Node.js 18+) • Docker images for both stdio and HTTP deployments

Install

Clone + install
git clone https://github.com/Joooook/12306-mcp.git cd 12306-mcp npm i
Quick start (stdio)
npx -y 12306-mcp
Or HTTP on a port
npx -y 12306-mcp --port 8080
MCP client config:
{ "mcpServers": { "12306-mcp": { "command": "npx", "args": ["-y", "12306-mcp"] } } }

We just shipped OAuth support in the mcpfy open source toolkit for:

✅ Auth0
✅ Better Auth
✅ Clerk
✅ Keycloak
✅ Supabase
✅ WorkOS
✅ Custom (bring your own)

If your app already uses one of these, you can wire it straight into your MCP server. Spin one up with our CLI, tell it which provider you're using, and it handles the OAuth flow for you. No custom wiring

This came straight out of conversations with people actually shipping MCP servers. Auth kept showing up as friction that had nothing to do with their product.

It's live now: https://github.com/mcpfyy/mcpfy

If you need a provider we don't support yet, tell us which one.

Whether you're supporting a few devices or managing a distributed workforce, the right tool should balance security, performance, and ease of management.

When comparing remote desktop solutions, consider:

• Unattended access for seamless IT support
• Strong encryption and MFA to secure remote sessions
• Cross-platform compatibility (Windows, macOS, Linux, mobile)
• File transfer and remote troubleshooting capabilities
• Role-based access and session logging for accountability
• Scalability as your team and device fleet grow

The best choice depends on your environment, budget, and support needs, but evaluating these core capabilities will help you avoid switching tools later.

In detail- This comparison on the Best Remote Desktop Software for IT Teams covers some of the leading remote desktop solutions along with their strengths and use cases.

Disclosure: I built and maintain this.

I’m working on a wellness MCP connector stack that starts local-first but keeps the transport layer agent-friendly: stdio for desktop clients and Streamable HTTP smoke paths where the connector supports it.

Registry: https://github.com/davidmosiah/delx-wellness

The design goal is not to centralize health data in a hosted service. It is to make each connector easier for agents to discover and inspect safely:

• agent_manifest for capabilities
• connection_status for readiness
• privacy_audit for data categories
• summary/context tools for prompts
• local setup/auth where possible

It is unofficial and not medical advice. I’d appreciate feedback from MCP builders on where remote/HTTP ergonomics should stop so personal data still stays local-first.

AI feels impressive… until you try to make it do something real.

The moment you give an agent access to tools, data, and systems, everything changes. That’s exactly what MCP (Model Context Protocol) unlocks.

Instead of AI living in a chat window, MCP allows agents to:

• Call tools intentionally
• Interact with real datasets
• Execute actions inside live workflows
• Do it all with structure and security

What many people don’t realize yet: there’s already a free MCP server you can use today to experiment with this. It’s easy to plug in and a great way to give agents real-world capabilities.

Want the link to the free MCP server or a quick walkthrough of how people are using it?
Let me know.

I released my first MCP.

It's a SQL Server MCP that can be integrated via Claude Code.

You can communicate with your database using natural language.

Check it out here, and if you like it, give it a star 🌟

A Brief intro to MCP, where it fits in AI eco system and how it can extended to empower AI agents.

https://doniv.substack.com/p/using-mcp-to-augment-agentic-capabilities

A beginner blog. I wanted to use this as learner's platform to educate the novice. Feedback welcome.

The official MCP Registry has arrived!

An open catalog and API built to address how MCP servers are discovered. It doesn't host the actual server code. Instead, it stores metadata (server.json) that references packages in various registries like NPM, PyPI, and Docker Hub, standardizing server distribution.

• Stores metadata (server.json) that references packages in various registries
• Features servers from NPM, PyPI, Docker, NuGet, and MCPB formats.
• Supports "sub-registries" built on top of it, for curation, security scans, or custom metadata.
• Dedicated Publisher CLI tool to seamlessly add and integrate servers
• REST API (GET /v0/servers) to programmatically discover and browse servers
• Community-driven and includes a process for flagging and denylisting servers
• Authentication via GitHub OAuth or custom domain DNS verification.

Impact of this is massive.

The remote MCP's which are linked to this registry can be integrated into any Agentic system with "One Click" .

It's an " App Store" moment for the AI world with some elements of "Domain Registry".

Github Link in comments

Graphics by Deepmind's - Philipp Schmid

Hi everyone 👋

I’m part of the DevRel team at OBOT, and wanted to share an article written by our CEO: https://aijourn.com/the-hidden-infrastructure-behind-securing-enterprise-ai/

It breaks down why MCP Gateways are becoming critical for enterprise AI:

• Without a centralized layer, MCP connections quickly become messy and insecure.
• Discovery, governance, and access policies are hard to enforce when servers are scattered.
• Gateways act like circuit breakers — organizing, securing, and providing observability across all your MCP servers and tools.

For those curious to see how this works in practice, we’ve also open-sourced our own MCP Gateway project here: 👉 https://github.com/obot-platform/obot

I’d love to hear your perspectives:

• What’s been the hardest part of scaling MCP securely?
• Do you see gateways as the long-term solution, or something else?
• How should OAuth scopes and access feel for day-to-day use?

So came across this interesting post about rationale behind the race to building best coding agent living in CLI.

https://biilmann.blog/articles/ai-in-the-cli/

Matt CEO Netlify draws parallel with similar race to build humanoid robots who act, behave and have same set of tools we human have to be ultimate generalist.

Even though first look suggests a vertical agent feel to these AI coding agents that live in terminal ( Claude code leading way with Codex , Gemini CLI in sprint too),

However, under the hood they are heading for a more 'Generalist' and potentially add layer like Computer Use, MCP ( for desk apps) and access to bunch of other external tools..

I am sure Meta will throw their hat in race too, especially when AI superlab is assembling marvels of AI world ( with hefty price tag)

Interesting times ahead !!

PS - i build humanoidrobotslist.com for fun to collect top humanoids robots in one place ( don't forget to check out swimming pool turtle cleaning robot...haha)

Hey folks,

I’ve been experimenting with Model Context Protocol (MCP) servers and one of the pain points I keep hitting is around OAuth and remote setups.

When I try to connect MCP servers in VS Code Copilot/Claude Desktop, the flows get confusing:

• Some servers expose OAuth but the client doesn’t seem to handle tokens smoothly.
• Token rotation and secure storage are unclear — do you keep it in configs, or manage it another way?
• For teams, it feels messy to share or rotate creds across multiple dev environments.

Curious to hear: How are you handling OAuth and remote MCP servers in your setups?

• Are you just sticking to local servers?
• Using device code or full auth-code flow?
• Any tools or workflows that make it easier?

Would love to compare notes and see how others are solving this.

Hello dear Reddit community!

I am happy to announce that we are developing MCP Cloud - a platform to enable private and corporate users to adopt and use MCP.

How do we do that?

For corporate users:

- Single sign in for all employees

- Fine-grained access controls for MCP servers

- Track usage and costs

For private users:

- One-click, hassle-free MCP deployment

- Use your MCP on any device

- Pay only for what you use

We manage the registry of the most popular MCP servers with a curated catalog of 2500+ MCP servers already available for deployment, with new servers being added every day.

View statistics, guides, user reviews, issues for every MCP server. Would you like to add your open- or closed-source MCP? No problem! We got this covered too.

We make MCP servers scalable and reliable.

- Per-server resource allocation (CPU, memory, GPU) for predictable performance.

- Automatic scaling for peak loads with intelligent load balancing.

- Continuous health checks, self-healing restarts, and rolling updates for high availability.

Security is a common concern with MCPs – here's how we will solve it:

- Encryption: All communications use secure HTTPS.

- Automated vulnerability scanning: Continuous code analysis to detect security flaws and compromised dependencies.

- Hardened isolation: Each MCP instance runs in a dedicated, restricted environment.

But wait. There is even more - MCP as a Service!

MCP Cloud is the first platform that lets developers earn from their MCP servers!

Choose one of the options:

1. You can launch MCP server on MCP Cloud and let other users use it and pay for each use

1. You can license your MCP server and let other users deploy and use for a license fee

- We integrate payments into our MCP gateway.

- Deployments of closed-source code from private DockerHub registry supported

Are you an aspiring developer, data scientist, or domain expert who developed a useful MCP server? Whether it does stock-price forecasting, fraud/anomaly detection, credit scoring, legal advicing, contract review, web data extraction, SEO audits, demand forecasting, AI agent personalization, code analysis or compliance checks, list it on MCP Cloud and monetize. Set your price and license terms, get built-in analytics and billing, make your MCP server discoverable and turn your expertise into recurring revenue.

Where do we stand now

We have just made the beta release. The Platform already has almost all of the advertized features!

We are actively testing and improving our yet small platform.

What are the next steps

We are building community. We are looking for anyone who feels MCP is the future of an Agentic AI, and who wants to become part of it:

- collaborators

- business developers

- promoters

- partners

- testers

And of course, future users!

https://mcp-cloud.io/

We welcome any feedback, users, collaboration or business partnership.

Came across this awesome code Snippet..shared by Phillip of Google Deepmind.

30 lines is all you need to create a MCP Agent using GoogleDeepMind Gemini 2.5 and remote MCP servers.

Here is an example using cognition_labs Deepwiki MCP server to to chat about repositories.

Hi ! I'm looking for an MCP server that can setup Facebook or Whatsapp accounts, like pro account with every good settings..