LLMs are getting better at drafting content, summarizing data, and answering questions. But they’ve had one limitation: they can’t access the tools and platforms you actually work in.
That changes now. tchop.io has released an open-source MCP server that connects AI assistants like Claude directly to your tchop organisation. No copy-pasting. No exporting CSVs. No switching tabs. You ask a question in plain language, and the AI pulls the answer straight from your live data. Or pushes any new content, message or comment.
What is MCP, and why does it matter?
MCP (Model Context Protocol) is an open standard that lets AI assistants connect to external services. Think of it as a bridge: on one side, your AI assistant. On the other, your tchop platform with all its channels, stories, users, and analytics.
Instead of telling an AI “here’s a spreadsheet of our content,” you can say: “Show me all stories published in our onboarding channel this month.” The AI queries your platform directly and returns the answer.
What the tchop MCP server can do
The MCP server gives small teams superpowers. Instead of clicking through dashboards, exporting spreadsheets, or switching between tools, you work through conversation — and the AI handles the rest.
Today, the server covers the foundations: browsing channels, searching content, reviewing users, and pulling analytics. But the architecture is built for much more.
The full scope of what becomes possible:
- Analytics and reporting — ask questions about engagement, active users, and content performance in plain language. No dashboard required.
- Content curation and aggregation — search across channels, find related content, surface what matters. Let AI compile and organize instead of doing it manually.
- Community insights — understand what’s happening in your community beyond content. See which posts spark conversation, identify your most engaged members, surface trending topics from comments and reactions. Turn raw interaction data into actionable insights about what your audience cares about.
- Automation — routine tasks like content audits, user activity checks, engagement monitoring, and community health reports can run as AI-driven workflows instead of manual processes.
- Content transformation — take existing content and repurpose it: turn a long article into a summary card, extract key points from a thread, or draft a push notification from a story.
The first release covers read access across your entire platform. Write operations, community interaction data, deeper analytics, and automation workflows follow soon. The direction is clear: your AI assistant becomes a full operator on your tchop platform — not just a viewer.
What this means for your team
The MCP server serves different roles depending on how you use tchop.
Internal communications teams
You manage an employee app for hundreds or thousands of people. Finding specific content or understanding engagement patterns usually means navigating dashboards and pulling reports manually.
Now you can ask your AI assistant: “Which channels have the lowest engagement this quarter?” or “Find all content about the new safety policy.” Soon you’ll also be able to ask: “Which posts got the most comments this month?” or “What topics are employees discussing in the feedback channel?” What used to take 20 minutes takes 10 seconds.
Brand and startup communities
You’re building a direct relationship with your audience, but you’re running lean. The MCP server lets you query engagement data, search for discussions, and review content without leaving your AI workspace.
“Show me the most active channels.” “Which posts sparked the most conversation this week?” “What are members asking about in the product channel?” Fewer dashboard sessions, faster decisions — and a deeper understanding of what your community actually wants.
Agencies managing client platforms
You operate multiple tchop instances for different clients. Checking in on each one means context-switching between dashboards and compiling reports manually.
The MCP server turns that into a conversation: “How many stories were published this month?” “What’s the comment activity like across channels?” “Summarize community engagement for the client report.” Operational efficiency across every client account.
News publishers
Your editorial team publishes across multiple channels. Keeping track of what’s live, what performs, and what resonates with readers is a daily task.
“Show me everything published in the sports channel today.” “Which articles are getting the most reader reactions?” “Pull active user numbers for the last 30 days.” Less editorial overhead, more time for journalism — and clearer signals about what your audience values.
Local and hyperlocal publishers
You’re a small team — maybe one or two people. You don’t have time for dashboards.
“How many readers does my main channel have?” “What did I publish this week?” “Are people commenting on the town hall story?” Your AI assistant becomes a second pair of eyes on both your content and your community.
Open source and ready to use
The tchop MCP server will soo be released open source on GitHub. It runs locally, connects via secure API credentials, and works with any MCP-compatible AI client. Setup takes minutes.
Where this is going
This is just the beginning. Soon you’ll be able to create and update content through AI conversations, monitor community engagement in real time, run automated reporting workflows, and manage your entire platform without opening the dashboard.
The vision: your AI assistant doesn’t just answer questions about your community — it helps you run it.
Want to connect your tchop platform to AI? Get in touch with us anytime! We will show you around and give you a quick demo!
