scalekit

A real working agent you can deploy

This repo uses a single SCALEKIT_USER_ID env var to simulate one user. In production, pass each user's real ID as the identifier on every Scalekit call, and send them an authorization link whenever their connector status is not ACTIVE. HubSpot's 30-minute token expiry is handled automatically.

01

Authorize, then orchestrate

main.py

Every connection is authorized once via a one-time link. Scalekit checks both HubSpot and Slack connections are ACTIVE before fetching: a connector that has lost authorization surfaces a new link immediately rather than delivering a partial digest. main.py runs on a daily cron and fetches all deals modified in the last 24 hours.

main.py

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tools = client.actions.langchain.get_tools(
    identifier="user@example.com",
    connection_names=["hubspot", "slack"],
)

02

Fetch recently modified HubSpot deals

fetch_deals.py

03

Detect changes via snapshot diff

detect_changes.py

04

Send personalized Slack DMs per owner

notify_owners.py

Why choose Scalekit

Delegated identity. Not service accounts.

Credentials never touch agent code or LLM context. The agent acts as the user, not as a shared bot.

Delegated OAuth - Agent reads your calendar, your inbox — scoped to the authorizing identity, not org-wide.

Credentials outside agent runtime - Tokens never touch agent code or LLM context. Both failure modes covered.

Token lifecycle automatic - Refresh, expiry, rotation across all connectors. One SDK call. Zero management code.

200+ prebuilt connectors - Google, Slack, HubSpot, GitHub, Jira, Notion, Salesforce — same auth pattern everywhere.

Agents that deliver CRM digests, without the auth plumbing

Two things you'd otherwise build: HubSpot OAuth with 30-minute refresh and Slack credentials per user. Handled.

OAuth flow per connector

One SDK call returns a delegated token for any connector. Google, HubSpot, Slack, same pattern across all 200+ connectors

tools = client.actions.langchain.get_tools(
    identifier=user_id,
    connection_names=["hubspot", "slack"],
)
agent = create_tool_calling_agent(llm, tools, prompt)

Secure token vault

Scalekit stores OAuth credentials outside agent code and outside LLM context. Both are separate failure modes. Both covered

client = ScalekitClient(
    env_url=os.environ["SCALEKIT_ENV_URL"],
    client_id=os.environ["SCALEKIT_CLIENT_ID"],
    client_secret=os.environ["SCALEKIT_CLIENT_SECRET"],
)
# Credentials never in agent code or LLM context

Token refresh logic

Token lifecycle handled automatically — expiry, rotation, re-auth — across every connector. Agent runs in 6 months. Same call works

# Day 1 or day 180 — same call works
tools = client.actions.langchain.get_tools(
    identifier=user_id,
    connection_names=["hubspot", "slack"],
)

Try other Agent Templates

Prebuilt agents you can ship today

Each one runs on delegated identity, scoped per user.

SALES

Sales call prep agent

Pull Granola notes and Attio contact history to draft a pre-call brief before every sales meeting. Zero rep input.

Granola

Attio

View agent

GTM

CRM AI agent

Log calls, update opportunity stages, and surface stalled deals across HubSpot or Salesforce. No manual data entry.

HubSpot

Salesforce

View agent

SALES

Deal intelligence agent

Combine Gong, Attio, and Slack signals to surface deal risks and next-best actions. Updated after every call.

SALES

Outbound prospecting agent

Build targeted prospect lists with Apollo, enrich with firmographic data, and draft personalised outreach. Runs on a schedule.

Apollo

View agent

GTM

Salesforce customer insights agent

Surface Salesforce account activity, NPS signals, and renewal flags into Slack threads for the account team.

Salesforce

Slack

View agent

SUPPORT

Support triage agent

Read Zendesk tickets, fetch runbooks from Notion, and route to the right Slack channel with a drafted response.

Customize the sample

Clone it and own it with connectors you choose

Don't sweat the integration. Point a coding agent at the repo. It clones, swaps in your connectors, and adds new steps for you.

1

Install a coding agent

terminal

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claude "Set up a CRM-to-Slack digest agent using HubSpot and Slack via Scalekit"

terminal

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codex "Set up a CRM-to-Slack digest agent using HubSpot and Slack via Scalekit"

terminal

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gh copilot suggest "Set up a CRM-to-Slack digest agent using HubSpot and Slack via Scalekit"

terminal

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Open Cursor Composer (Cmd+Shift+I) Paste the prompt from the Prompt tab

terminal

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npx skills add scalekit-inc/skills --skill setup-scalekit

2

Give it this prompt

prompt

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Clone github.com/scalekit-inc/python-connect-demos/langchain. Set connection_names = ["hubspot", "slack"]. Build a CRM digest pipeline: fetch HubSpot deals modified in the last 24 hours, diff against a local snapshot, group changes by owner, send a personalized Slack DM to each rep using their own Slack identity (not a bot). Map HubSpot owner IDs to Slack user IDs per tenant. Set SCALEKIT_ENV_URL, SCALEKIT_CLIENT_ID, SCALEKIT_CLIENT_SECRET in .env.

CRM digest agents that notify owners on-behalf-of your users

How the agent detects CRM changes and notifies each deal owner in four steps

A real working agent you can deploy

Delegated identity. Not service accounts.

Agents that deliver CRM digests, without the auth plumbing

Prebuilt agents you can ship today

Clone it and own it with connectors you choose

Build your own
‍multi-connector agent

CRM digest agents that notify owners on-behalf-of your users

How the agent detects CRM changes and notifies each deal owner in four steps

A real working agent you can deploy

Delegated identity. Not service accounts.

Agents that deliver CRM digests, without the auth plumbing

Prebuilt agents you can ship today

Clone it and own it with connectors you choose

Build your own‍multi-connector agent

Build your own
‍multi-connector agent