The MCP Servers I Actually Use With Claude in 2026

David Hamilton — Sat, 30 May 2026 20:28:20 +0000

The MCP ecosystem went from a handful of servers to thousands in under a year. Most of them are demos you connect once and forget. A few have quietly become part of how I work every day.

This is the short list that earned a permanent spot in my Claude setup as a solo founder, grouped by what I am actually trying to get done. No affiliate links, no rankings for the sake of it. Just the ones I would reconnect first on a new machine.

The two every setup needs

Filesystem (the official server) lets Claude read and write local files. Boring, essential, and the first thing I connect anywhere.

GitHub brings issues, PRs, and code search into the chat. If you write code, it is the highest-leverage connection after filesystem.

Marketing and growth

This is where MCP stopped being a novelty for me and started saving real hours.

The Google Search Console MCP pulls my live query and impression data into Claude, so I can ask "which pages slipped this week" and get an answer without opening the GSC dashboard.

The Google Analytics MCP server does the same for GA4: sessions, events, and conversions, all queryable in plain English.

If you run sales, the HubSpot MCP server lets Claude read and update contacts, deals, and companies. That turns "draft a follow-up for everyone in the pipeline who went quiet" into a single prompt.

Connecting all three means one question can span search data, analytics, and CRM, and Claude stitches it together. That is the part that still feels like magic.

Automation glue

The n8n MCP server is the one I reach for when a workflow needs to run on a schedule instead of whenever I happen to be in a chat. Weekly digests, smart routing, alerts. n8n already connects to almost everything, and MCP lets Claude drive it.

Knowledge and memory

Claude forgets everything between chats. These servers fix that.

Obsidian and Notion servers expose your notes so Claude can search them and write back.

ContextBolt (full disclosure: I built this one) gives Claude semantic recall over the things I save from X, Reddit, and LinkedIn. I save a thread, and three weeks later I can ask "what was that take on pricing I saved" and get it back with the source. It exists because I kept saving things and never finding them again.

How to pick

Two rules that have served me well:

Connect for a job, not for a demo. A server you use once is clutter.
Read the setup notes before you wire up auth. Half of these put a token in a config file or a URL, and the gotchas vary by server.

That second rule is why I keep a running directory of the best MCP servers with per-server setup steps, auth notes, and the gotchas I hit, sorted by category. It started as my own notes. Now it is a public MCP server directory you can browse by job instead of scrolling one giant list.

If you are just getting started, connect filesystem, then add one server for the job in front of you. Build from there.

I deleted the chat feature from my own AI product. Here's what I built instead.

David Hamilton — Wed, 06 May 2026 22:09:56 +0000

I deleted the chat feature from my AI product.
The irony writes itself. A small Chrome extension whose entire purpose is bringing AI to your saved content. The first thing I cut was the AI-shaped feature.
It was the easiest call I've made on this build.
Three reasons. Each one obvious in hindsight.
API costs. A back-and-forth chat conversation eats £1-2 a month in tokens per active user. My Pro tier is £4 a month. The maths doesn't work the day you launch. It only gets worse with scale.
Product bloat. A chat box is the kind of thing you build because every other AI product has one. It looks like the AI feature. It isn't.
V2. If users actually want to chat with their bookmarks, they'll tell me. I'd rather build it then than guess now.
The product is called ContextBolt. It captures your bookmarks from X, Reddit, and LinkedIn. It auto-tags each one with Claude. And then it does something most products in 2026 still don't.
It exposes itself to Claude.
Pro users get a personal MCP endpoint. They paste one URL into Claude Desktop. From that moment on, Claude can search their entire bookmark library mid-conversation. You ask Claude something. Claude reads your saved content. The answer arrives with the context already in it.
The dashboard I built first turned out to be the legacy interface. The MCP endpoint is the actual product.
That's the irony resolved. The chat box was never the AI part. The integration was the AI part. I just couldn't see it until I deleted what I thought it was.
Here's the part I find harder to explain.
I'm one person. I have a day job. I get about ten hours a week on this thing, mostly evenings and weekends. The amount of code in this product is not the amount of code one person could write in ten hours a week.
I didn't write most of it.
Claude did.
I use Claude Code. I describe what I want in plain English. Claude writes the service worker. Claude writes the Cloudflare Worker. Claude writes the React dashboard. Claude writes the SQL migrations. I read what comes back, push back where the taste is off, and ship it.
Two days ago Google approved the extension on the Chrome Web Store. I downloaded my own production build. Within an hour I'd found four bugs in real-world testing. The LinkedIn dashboard didn't refresh on save. The X popup showed a scraped count instead of a deduplicated one. The auto-scroll stalled at twenty bookmarks. The licence-key save flow failed silently.
I described each symptom out loud. Claude found the wrong file (a content script that was dead code, while the loaded one had no listener). Claude wrote each patch. We shipped five extension versions and two worker deploys that evening. I never opened a debugger.
That is what working with Claude actually looks like in 2026. It is not autocomplete. It is a colleague who reads the whole codebase faster than you can blink, fixes the thing, and writes the commit message while it's at it.
The infrastructure is the other surprise.
The whole product runs on Cloudflare. Pages for the website. Workers for the API. D1 for the database. KV for the rate limits. Vectorize for the semantic search. There is no AWS bill. There is no Vercel bill. There is no managed database bill.
Including Claude API spend, the entire stack costs me under £5 a month at current usage. I keep waiting for that to be a lie. So far it isn't.
The marketing flywheel is the same recursive shape.
Thirty-three blog posts on the site. Sixty-six programmatic SEO pages. Every post drafted with Claude. Every meta description checked by Claude. Every internal link suggested by Claude. The site's scheduled tasks run with Claude reading my Search Console and writing the next thing to fix.
I review. I edit. I ship.
The asymmetric stack is the only reason a one-person, ten-hour-a-week build can keep up with funded teams. Claude does the parts that scale linearly with effort. Writing. Debugging. Testing. Drafting. I do the parts that don't. Taste. Decisions. Picking what to ship. Picking what to delete.
I keep coming back to that last one.
The chat box was never the AI part. It was the legacy UI we used while we figured out what the AI part actually was. The AI part is the integration. The AI part is your existing tools getting access to context they didn't have before.
Most AI products in two years will look like ContextBolt. A small piece of software that does one thing well and exposes itself to whatever model the user already pays for. The product team doesn't have to ship the chat box. The user already has one.
That's why deleting the chat was easy. Once you see it, you can't unsee it.
ContextBolt is live on the Chrome Web Store today. The site is at contextbolt.com. If you save more than you read, you'll feel it the first time Claude finds something for you that you'd already given up on.
I'd love to know what you'd connect it to.