Playbook · the problem

Nucleus tried & tested

Nucleus + ClickUp task flow

ClickUp Brain only sees ClickUp.

ClickUp Brain reasons over your tasks and docs, but it cannot reach your CRM, meeting recordings, or shared drives. Brain MAX adds Google Drive and GitHub, but anything outside that fixed list is still invisible to your agent.

Every cross-tool question means switching tabs and copy-pasting context by hand.

By Nucleus Team

The architecture

Without the layer

ClickUp

tasks + docs

ClickUp Brain

sees ClickUp only

No shared layer

other tools stay invisible

ClickUp Brain reasons over tasks and docs inside ClickUp, but your CRM, meeting notes, and shared drives stay invisible.
Brain MAX adds Google Drive and GitHub, but it still cannot reach your help desk, Fathom recordings, or arbitrary SaaS tools.
Every cross-tool question means switching tabs and copy-pasting context by hand.

With Nucleus

You update a task

in ClickUp, as normal

Nucleus syncs it live

into the context layer

Nucleus joins the context

task + docs + CRM, together

Your agent acts

grounded, current answer

Nucleus indexes ClickUp alongside Google Drive, Slack, Fathom, Attio, and any MCP-connected source.
One prompt joins tasks, docs, meeting notes, and CRM records without leaving the chat.
Context stays live: update a task in ClickUp and the layer reflects it on the next query.

What stops a wrong answer becoming permanent

COVE, chain of verification

01Decomposesplit into atomic claims

02Retrieve per claimone claim at a time

03Verify alonejudged on own evidence

04Scoreper claim, not per answer

05Attributesources on, uncertainty shown

The command

Per prompt · type it in any chat

use Nucleus for context

Once it's in your settings, every task starts grounded. You can still say use Nucleus at Attio to point it at a specific source.

Before you start

A ClickUp workspace
A Nucleus workspace

Steps

Open Integrations in Nucleus

Open the Nucleus dashboard and click Integrations in the left sidebar. You will see your current connectors and a grid of available integrations.

The Nucleus dashboard Integrations page showing connected services and the Add Integration card. — The Integrations page in your Nucleus dashboard.

Add a custom MCP connector

Click Add Integration at the top of the page. In the dialog that opens, scroll to the MCP Servers section and click Custom connector.

The Add Integration dialog showing Cloud Storage, Databases, and MCP Servers sections with a Custom connector option. — Click Add Integration, then Custom connector under MCP Servers.

Enter the ClickUp MCP endpoint

Fill in the form with the following values:

Name: ClickUp
MCP Server URL: https://mcp.clickup.com/mcp
Authentication: OAuth (auto-discover), or Bearer token if OAuth is not yet available for your workspace

Click Add server to save the connection. If you chose OAuth, you will be redirected to ClickUp to authorize. If you chose Bearer token, paste your ClickUp API key in the token field.

The custom MCP server form filled with Name set to ClickUp, URL set to https://mcp.clickup.com/mcp, and Auth set to OAuth auto-discover. — Fill in the ClickUp MCP endpoint and choose your auth method.

Verify and start querying

Once connected, Nucleus indexes your ClickUp tasks and docs into the context layer. You can now query across ClickUp and any other connected source, such as Google Drive, Slack, or your CRM, in a single prompt.

Try these in your agent or chatbot

These sample queries work because Nucleus joins context from ClickUp with your other connected sources. Copy any of them into a chat that has Nucleus connected.

"What tasks in the current sprint mention the payments API, and do any of our Google Drive design docs cover the same flow?"
"Summarize every task assigned to me that is overdue, and pull in any related Slack threads from the last week."
"Draft a standup update from my ClickUp tasks closed this week and any Fathom meeting notes tagged with the same project."
"Which open tasks have no linked doc or design spec in Google Drive? List them so I can fill the gaps."

Each query crosses at least two sources. That is the point: Nucleus holds the joined context so your agent does not have to.

Give your AI the same context you have

Connect your sources once. Every workflow, agent and assistant reads the same grounded layer, and everything written back is checked before it lands.

Create your Nucleus

Terms

Context Layer: A context layer is the persistent, source-grounded organizational memory that sits between an organization's data and whichever model it uses, so every assistant and agent reads the same weighted, reconciled picture instead of re-deriving it per tool. It exists independently of any single agent or session. It is not a vector store, which retrieves passages without reconciling them, and not agent memory, which belongs to one agent and resets with it.
Understanding Layer: The understanding layer is Nucleus's name for the context layer it builds: the layer between organizational data and foundation models where scattered sources become one coherent, verifiable account of what an organization knows. Storage holds the data and the model does the reasoning; the understanding layer makes the two compatible, adding memory, relationships across sources, grounding, and verification. It is an implementation of the context layer category, not a competing concept.
Organizational AI Memory: Organizational AI memory is the persistent, permission-aware record of what an organization knows, decides, and corrects, held so any AI system can retrieve it at inference time. It is not a knowledge base, which stores content; memory also preserves who established what, when, and on what evidence. And it is not agent memory, which belongs to one agent and resets with it. Memory for one agent is not memory for an organization.
Grounding: Grounding is supplying a model with the sources it should rely on before it answers, so the output is constrained by evidence rather than by the model's guesswork. It improves what goes into generation; it does not test what came out, which is verification's job. The two are parallel disciplines, not interchangeable ones: a well-grounded system can still produce a fluent claim no source supports.
AI Memory: AI memory is context that survives across sessions and across tools, so an assistant does not start from zero each time or relearn what another tool already knows. It is not a longer context window, which extends a single session rather than persisting anything, and not chat history, which replays what was said rather than retaining what was established. Memory for one agent is also not memory for an organization; the two are different layers of the stack.
Drift: Drift is an AI system's understanding diverging from the state of the thing it is reasoning about, so answers that were correct become quietly wrong as the underlying systems change. It is not the same as context rot. Rot degrades within a session as context is displaced; drift accumulates across sessions as the world moves and the system's picture does not.