Datapacks

A datapack is the isolated store for one body of agent context. This page is how you create one, connect to it, share it, and remove it.

Create a datapack

The first time you sign in to the Meko portal, Meko walks you through the steps to create your default datapack (meko_default_datapack) and connect it to your client.

To create additional datapacks:

1. In the Meko portal, navigate to Datapacks.
2. Click Add Datapack.
3. Follow the instructions in the configure wizard.

If Meko can't finish setting up the datapack's tracing project, creation fails with Could not finish setting up the datapack; nothing was created. Please retry. Nothing is left behind, so retry with the same name.

You can create more than one datapack at the same time, up to your plan's datapack cap.

Reach a tier limit

The Free tier includes limits on datapack creation, knowledge base storage, number of conversations, and WorkbenchLM token usage. When you exceed a limit, Meko displays a corresponding message. Click Upgrade to Standard on the message banner to open Settings > Pricing with the Standard plan selected.

In Meko Cloud, Standard is $25 / month. On Settings > Pricing, choose Stripe or AWS Marketplace.

An account pays through one of them. Stripe Checkout does not start when the account already has an active AWS Marketplace subscription. Cancel that subscription first. If you already pay through Stripe and then subscribe on AWS Marketplace, cancel the Stripe subscription in Manage subscription. The AWS plan takes over when the Stripe subscription ends.

After you subscribe on AWS Marketplace, click Set up your account. If you skip that step, the plan stays on Free. After Stripe Checkout, reload Settings to see the updated plan. See Meko pricing.

You cannot upgrade from Standard using the Marketplace. To upgrade, choose Talk to our team.

Free tier has the following limits:

• 10 datapacks
• 100 MB of knowledge base storage
• 1,000 conversations
• 10 million WorkbenchLM tokens

Manage datapacks

Manage your datapacks from the Datapacks page in the Meko portal. Datapacks lists all your datapacks. From here you can add and share datapacks.

Select a datapack to view the conversations, memories, learnings, and knowledge the datapack holds.

From here, you can review and promote learnings to knowledge.

After you create a datapack:

• Share it. Invite team members or share a link. See Share a datapack.
• Manage access to your shared datapack by assigning roles. See Manage access.
• Add it to a project. A project groups datapacks that work toward one outcome, while keeping each datapack independent. See Projects.

Delete a datapack

Only the owner can delete a datapack.

Open the actions menu (the gear next to Share) and choose Delete [datapack name], then click Delete.

You can't delete meko_default_datapack, the datapack Meko created when you signed in.

You can delete a datapack when tracing is unavailable.

Connect via MCP

Each datapack exposes an MCP server that agents use to interact with their data.

To connect an external MCP client (Cursor, Claude Code, and so on), you need:

• The MCP server URL, https://mcp.mekodata.ai/mcp (the same for every datapack and user).
• A user API key: a long-lived key you generate under Settings > API Keys in the portal (values start with mko_tkn_).

Agents select the datapack to connect to by passing the datapack_id inside each MCP tool call, not by using a different URL per datapack.

When you create a datapack in the Meko portal, Meko provides instructions to connect your datapack to your agent automatically. The connection commands are also available under Connect in the Meko portal.

You can also configure clients by manually adding this configuration to your coding agent or agent framework. See Connect your agents.

Automatic capture and datapack pinning

When you have multiple datapacks, you designate one as your active pin - the default datapack where Meko saves conversations and memories. If you only have one datapack, Meko uses it automatically.

How to change your pin

Ask your agent in plain language:

Switch my Meko datapack to research

Or invoke the selector skill directly:

# Claude Code
/meko-agent-skills:meko-select-datapack

# Claude Desktop
/meko-select-datapack-desktop

The selector shows 10 datapacks at a time, newest first. It shows your role on each row, such as owner or viewer, and marks the current pin.

Reply with a number to pin that row, part of a name to search, or next / prev to change pages. A name reply searches the whole account, including rows that are not on this page. Reply with clear or none to drop the pin and use your account default.

Pins apply to new conversations only

When you switch pins: Your current conversation stays in its original datapack. The new pin takes effect only when you start a new chat. Existing conversations never move between datapacks.

Example: You're chatting in the "research" datapack. You say "Switch my pin to personal-projects." Meko updates the pin, but the current conversation keeps writing to "research." Your next chat will use "personal-projects."

How the pin persists across sessions

Claude Code: The pin is stored per project and survives restarting Claude Code, clearing your transcript, and opening another window in the same repository. Different projects can have different pins.

Claude Desktop: The pin is stored in Meko memory and survives across all Desktop conversations until you change or clear it.

If your pinned datapack is deleted or you lose access, Meko fails gracefully rather than silently writing elsewhere. Run the selector to pick an accessible datapack, or clear the pin.

Share a datapack

You can share a datapack by inviting people, or by sharing a link. Only datapacks in Meko Cloud can be shared.

To author a shareable datapack as reviewed source in a repository instead of through the portal, see Publish a public datapack.

An owner or a maintainer can invite people. In the portal, only the owner can create, copy, change, turn off, or reset the share link.

On the datapack, Share opens a menu:

• Invite People opens the invite form.
• Create share link is shown when the datapack has no link. Copy share link is shown when the link is on. Only the owner sees these.
• When a link exists but is off, that item opens the Share page so the saved role stays as it is.
• Settings opens the Share page.

When you add a member, you assign a role. To change that role or remove someone, see Manage access.

When you share a datapack that sits in a project, the recipient finds that project on Projects, under Shared with me. See Projects.

Invite team members

To invite colleagues to your datapack:

1. Open the datapack and click Share, then Invite People.

2. Under Invite humans, provide one or more Email addresses separated by commas, spaces, semicolons, or new lines, or click Upload CSV.

   A CSV can include a header row where one column is an email column. A file Meko cannot read as text shows Could not read file. Export it as CSV and upload it again.

3. Choose a Role for everyone in this list: Viewer, Contributor, or Maintainer. The role applies to every address in the batch.

4. Click Send invite. With more than one address, the button shows the count, such as Send 2 invites.

One batch accepts up to 50 addresses. Meko displays an error if you exceed the limit. To invite more than 50, split the job into multiple batches.

Meko reports a result for each address. A row with no valid email is skipped. Inviting someone who already has access does nothing.

Pending invites are listed under Pending, where you can resend or revoke invites that have not been accepted.

Share a link

Each datapack has one share link. In the portal, only the owner manages it.

To create the link:

1. Open the datapack and click Share, then Create share link.
2. Set Role joiners get to Viewer or Contributor. A link cannot grant Maintainer.
3. Click Create and copy link.

If the link is already on, click Share, then Copy share link.

To change a link that already exists, click Share, then Settings. On the Link sharing card:

• Turn Anyone with the link can join off to stop new people from joining.
• Choose Viewer or Contributor to change the role.
• Click Copy link to copy the URL.
• Click Reset link and confirm Reset the share link? to replace the URL. The old link stops working.

A person who is signed in and opens an active link joins immediately and opens the datapack. A person who is not signed in signs in or signs up first, then joins. They do not need an email invite.

Turning the link off stops new people from joining. People who already joined keep access.

Changing the role also changes it for people who joined through this link and still have that role. If their role was changed later, they keep their current role. The Link sharing card shows how many have joined.

A link that is off or unknown shows This link isn't available. Someone who was removed sees You were removed from this datapack. The link does not add them again. An owner has to invite them.

To publish a datapack as reviewed source under version control, rather than managing it by hand through the portal, see Publish a public datapack.

Manage access

An owner or a maintainer manages who can use a datapack. A viewer does not see the member list.

To invite someone or share a link, see Share a datapack.

Find a member

1. Open the datapack and click Share, then Settings.
2. Under Members, search by name, email address, domain, or role. The field says Search name, email, domain (@company.com), or role.
3. Filter the list by role. All roles shows everyone.

View all opens the Members page. The same list is on the datapack's Members tile.

Change a role

On Members, an owner or a maintainer chooses a role for another member. You cannot change the owner's role, or your own.

Meko shows Role updated. If the change does not go through, it shows Couldn't update role.

Changing a role from the Members card on the Share page asks you to confirm Update member role.

Remove a member

On Members, click Remove on that person's row.

The dialog title is Remove followed by their name. It says they lose access to the datapack right away and can rejoin only through a new invite. Click Remove.

The share link does not add them again. See Share a link.

Datapack roles

When you add a member, you assign them a role: Viewer, Contributor, or Maintainer.

• View: read knowledge-base material, memories, and conversations your deployment exposes for that datapack.
• Add memories: create new memories. Contributors can do this, but cannot write to the knowledge base directly.
• Add/edit knowledge base: upload or modify knowledge-base content. Requires Maintainer.
• Promote: elevate memories into shared knowledge. Requires Maintainer, or the datapack owner.

What a viewer can do

A Viewer can read the datapack.

In the portal and the REST API, a viewer sees the knowledge base, collective memory, conversations, and memories.

A viewer does not see who started a conversation, who added a memory, who uploaded someone else's file, or who promoted a memory.

A viewer does not see the member list. The Share page says You have viewer access to this datapack. Owners and maintainers manage who it is shared with.

Through MCP, a viewer can search the datapack.

Creating or changing a conversation or memory returns read_only_access.

Installer 2.5.0 holds automatic capture for that datapack and reports read_only_access the next time you start a session, instead of retrying every few minutes. See Capture won't save because you are a viewer.

A viewer can't upload artifacts or knowledge-base files.

A viewer can still delete their own memories, conversations they started, and knowledge-base files they uploaded. On Memories, Delete is on the viewer's own rows created on or after September 9, 2026. See Delete a memory.

A member whose role changed to Viewer can still remove what they added before.