Structure your context. Share it across your team and agents.

Midland is a shared home for your context, kept current and connected to your AI tools through one MCP.

Free during the beta. You can also for self-hosting, or book a call for an assisted roll-out.

Making AI work useful beyond the session.

I designed Midland after months of trying out different memory systems.

Each one worked at the start, then drifted and needed more and more maintenance. I never trusted any of them enough to roll out to clients or coworkers. If you've had the same experience, Midland is designed for you.

I use Midland to take on work with more moving parts than I can keep in my head. It gives my agents a place to find earlier decisions, instructions, and details I might otherwise forget to bring into the next task.

Midland is a shared layer that structures your context, shows who owns each part and when it is due an update, and serves it to any AI session.

I built it for small teams without data engineers, who would rather spend their time and tokens on agents for their own business than on the plumbing under them.

I want every model you use to know your business from its first session, as if it had been trained on it.

Now I am opening up the beta.

GTM playbookWrite the newsletterNewslettersFeature ideas

File

GTM playbook

How we take a release to market: who it is for, what we say, where we say it and what we measure. Read before planning a launch, a post or a newsletter.

Owner

Sarah

CategoryMarketing

Update expectationEvery quarter

Read accessAll members

ActivityView

Linked3

Version 9Sarah, 1w ago

Who it is for

Teams of five to fifty that already work with AI every day.
The person who sets up their tools, not the buyer.

Channels

The newsletter, once a month, to every workspace owner.
A launch post for anything a customer would notice.
The changelog for everything else.

Skill

Write the newsletter

Drafts the monthly customer newsletter from the changelog and the playbook's message, then saves the issue to Newsletters. Run it on the first Monday of the month, from any AI tool.

Owner

Eric

CategoryMarketing

Update expectationEvery month

Read accessAll members

ActivityView

Linked4

Version 5Eric, 4d ago

Read first

GTM playbook, for who we write to and what we say.
Changelog, for what shipped since the last issue.
Brand voice, for how we sound.

Steps

Lead with the one change customers will notice most.
Link each change to its changelog file.
Save the issue to Newsletters once Sarah says yes.

Collection

Newsletters

One file per issue as it was sent: the subject, each section and its links. Saved by the Write the newsletter skill. Read for what customers have already been told.

Owner

Sarah

CategoryMarketing

Update expectationEvery month

Read accessAll members

ActivityView

Linked3

Entries18

November: bulk import and shared views4d ago by Eric
October: search that keeps up1mo ago by Eric
September: single sign-on for teams2mo ago by Sarah
August: a faster first day3mo ago by Eric

Collection

Feature ideas

One file per idea from customers and the team: the problem, who asked and how often. Read before planning the roadmap or answering a feature request.

Owner

Priya

CategoryProduct

Update expectationEvery week

Read accessAll members

ActivityView

Linked3

Entries31

Bulk edit tags from the list1d ago by Priya
A weekly digest for owners3d ago by Marcus
Import from Notion1w ago by Sarah
Shared views for guests2w ago by Priya

Turn AI output into reusable team knowledge.

AI sessions and automated agent runs produce insights worth keeping. Give agents rules for where to save them, how to write them, and what existing context to update or link.

Automations to keep context current and trustworthy.

Routine jobs scan your context for outdated information, contradictions, and content that has been superseded. Flags travel with the context to all your agents, so they can investigate and resolve issues as they work.

Get a bird’s-eye view of your company’s context.

See how your context grows, changes, and is used. Group it by category or type, and filter by what’s new, most or least read, and most or least updated.

Built and maintained so you don't have to.

Spend your time and tokens on your own work, not on the plumbing underneath that connects your team’s AI.

Common problem	How Midland helps
Common problemContradicting answers show up depending on who asks and which tool they use	How Midland helpsMidland flags the conflict, its owner and the timestamps so every connected agent sees it before repeating the answer.
Common problemUseful context stays stuck with the person who created it	How Midland helpsOne structured layer serves the same current answers, skills and terms to Claude, Codex and any MCP tool, so the rest of the team inherits the setup the power user built.
Common problemYesterday’s decisions keep getting treated as today’s truth	How Midland helpsWhen a new decision is saved, Midland surfaces the older claims it replaces. Update expectations, ownership, scheduled Loops and control questions keep agents off the superseded answers.
Common problemThe way the team organises knowledge stops working as soon as the work changes	How Midland helpsEvery item says what it is and how to write to it, so the layer stays coherent as new decisions and use cases appear.
Common problemEverything useful produced in a session dies with the chat	How Midland helpsAgents follow rules for where plans, reports, transcripts and customer emails belong, how to write them, and which existing items to update or link, so session output becomes reusable shared context.
Common problemNo one is clearly responsible for keeping the shared layer honest	How Midland helpsEvery item has an owner, access rules and a clear update expectation. Agents and the overview show who is responsible and when something is past due.
Common problemKeeping the context layer usable eats the time and tokens meant for actual work	How Midland helpsBuilt-in skills let any connected agent set up the layer. Loops and automated writers handle the ongoing checks so people spend tokens on their own work.
Common problemA growing library of markdown files makes results worse instead of better	How Midland helpsYou choose what to save and can archive what is no longer useful. Midland organises the rest into named items with descriptions, so agents can find and read what is relevant to the task.
Common problemYou cannot see what an agent actually read, wrote or relied on	How Midland helpsEvery item carries source, owner and timestamps. Problems surface inside the agent’s work, and the overview shows what is being used.
Common problemEach AI tool starts from a different, incomplete picture of the team	How Midland helpsWorks in the AI tools you already use via MCP. The same setup is managed from one place and available in every connected session.
Common problemManaging a shared Git repo means handling access, merge conflicts and maintenance	How Midland helpsMidland hosts your context in the cloud, manages access and runs checks for issues. A planned automatic backup will copy workspace-wide content to a GitHub repo you own, without merge conflicts. Your content remains yours.
Common problemPast versions vanish and there is no reliable way to go back	How Midland helpsEvery version is kept, so you and your agents can look back at how a file has changed. If an update removes something you still need or takes the content in the wrong direction, open its history and restore an earlier version.

Built by and for AI-native teams usingClaude, and sometimes ChatGPT.

Get started with Midland.

Set up your workspace and give your team and agents shared context.

2 minCreate your workspace

Give your team and agents a shared home for knowledge, decisions and skills. Keep what you learn together, so everyone can find it and build on it.

Start now

4 minConnect your AI tools

Add the MCP to the AI tools your team already uses. Share the same context and instructions across tools, so useful knowledge carries from one session to the next.

20 minRun /setup. Start small.

Your agent checks your current setup, then guides. Turn what you already have into structured, actionable context, with sources, timestamps and instructions attached.

1 minInvite your team

Invite teammates with one click. An email link takes each of them through onboarding, and you choose who can see and update which parts of your context.

4 minConnect GitHub repo

Connect your team's private GitHub repository to back up your workspace every night. You own all your content. Midland just handles the structure and maintenance.

Frequently asked questions.

Find answers to common questions about Midland.

What is Midland, and why would a team use it?

Every AI tool your team uses starts from zero. It guesses what your words mean, which numbers count and how you like things done, and each person corrects it in their own way. Midland is one place where your team writes those things down once, each with an owner. Every AI tool you connect reads from the same place, so the answer no longer depends on who asks or which tool they use.

How is this different from a shared drive or a wiki?

A drive or a wiki is built for people to browse. It holds everything, often in several versions, and an AI searching it finds whatever matches, old or new. Midland holds only what your team has agreed is the answer, kept short, with an owner and a note on when to use it. Keep your full documents where they are, and put the agreed answer here.

Which AI tools does it work with?

Any AI tool that lets you add a custom connector (often called an MCP connector). That includes Claude, Codex and most other major AI tools, though some allow custom connectors only on certain plans, so check yours. Adding Midland takes a few minutes. Automated jobs can write to it too, for example a nightly job that records a number.

Do I need to be technical?

No. You use Midland through the AI tool you already have, in plain language: "Set up Midland for our team", "What does active client mean here?", "Save this to Midland." Someone adds Midland to your AI tool once, the way you would add any other connector. A web app lets you look through everything and change settings.

Is our data safe, and is it used to train AI?

Your content is kept safe and stays private to your workspace. It is stored in Sweden, in the EU. We do not train AI models on it, and Midland does not currently send it to any AI model provider. If that changes, we tell you first. When your AI tool reads from Midland, that tool handles what it reads under your agreement with its provider.

Isn't this one more thing to keep up to date?

Yes, a little. In return you keep a few things up to date in one place, instead of correcting every AI in every chat. Keep it small: only what people actually ask about, each with one owner. If nobody would notice an item was wrong, it probably does not belong here. Loops, scheduled checks that take on part of the upkeep, are coming. Until then, each item's owner keeps it current.

How long does it take to get going?

Adding Midland to your AI tool takes a few minutes. The first setup session leaves you with a handful of items the whole team can use. The value shows once people ask questions their AI can now answer, and save new things as they come up.

View all

Hosted

Create a workspace and connect your first tool. Free during the beta.

Create workspace

Self-hosted

Run Midland on your own infrastructure. The code will be open source. Leave your email for early access.

Assisted roll-out

We help your team structure its context into one shared layer.

Contact