What is the Clearskies Customer Context Graph?

The Customer Context Graph unifies CRM, call transcripts, email, calendar, and Slack into a single queryable layer with resolved identities, chronological timelines, and detected gaps. Instead of querying five systems separately, your AI gets one pre-resolved view of every customer, deal, and relationship.

How is a context graph different from individual connectors?

Individual connectors query each system separately — 5 to 15 retrieval calls, 50,000 to 100,000 tokens per query — and the AI has to guess how the data connects. A context graph resolves identity, timeline, and relationships before the AI sees a question. One connection, approximately 2,000 tokens, same answer every time.

What AI tools does Clearskies work with?

Clearskies is model-agnostic. It connects to Claude via MCP (Model Context Protocol), ChatGPT, and any LLM or AI tool that supports API or MCP integration. Confirmed clients include Claude, ChatGPT, n8n, and Retool.

What systems does Clearskies connect to?

Clearskies connects to Salesforce, HubSpot (CRM), Gong and Scratchpad (call transcripts), Google Workspace and Microsoft 365 (email and calendar), Slack (messaging), and Snowflake (data warehouse). No custom engineering or field mapping required.

How does Clearskies pricing work?

Usage-based pricing with zero user license fees. No per-seat charges, no platform fee. Free to start. Add your whole team without per-seat costs.

Integrations · MCP servers

The MCP server for your customer stack.

Clearskies is the MCP server for Salesforce, HubSpot, Gong, Slack, Gmail, Outlook, Pylon — every system that touches your customer — connected to Claude, ChatGPT, Cursor, n8n, and any MCP-compatible AI through one endpoint.

Identity resolved, timelines built, gaps detected — before any AI queries it. Connect once. Build anywhere.

What this is

One MCP endpoint. Every system behind it.

MCP — the Model Context Protocol — is the open standard for connecting AI to external data. Instead of wiring up Salesforce, HubSpot, Gong, Slack, and email one at a time inside Claude or ChatGPT, you connect them once to Clearskies and point any MCP-compatible AI at the Clearskies endpoint.

Behind that endpoint, Clearskies resolves identity, timelines, and relationships across every connected system. So a question like “what’s the status of the Acme deal?” returns one coherent answer built from CRM, calls, email, and Slack — not five fragments the model has to stitch together.

See how it works in detail

CRM

HubSpot

Connect your HubSpot portal once.

CRM

Salesforce

Connect your Salesforce org once.

CRMRoadmap

Attio

Modern CRM context flowing into the graph alongside calls, email, and Slack — on the roadmap based on customer demand..

Calls

Fathom

Fathom transcripts and meeting summaries flow into the graph and get resolved against the right deal, contact, and account automatically..

Calls

Gong

Every call transcript, summary, and identified moment.

Calls

Scratchpad

Calls, notes, and pipeline updates from Scratchpad join the context graph so AI works from the same signal reps work from..

CallsBeta

Granola

Granola meeting notes, summaries, and action items flow into the context graph — resolved against the right deal, contact, and account automatically..

CallsRoadmap

Fireflies

Fireflies meeting transcripts and summaries — on the roadmap based on customer demand..

Email

Gmail

Customer email threads — across every rep — resolved to the right deal and contact, with content searchable in the graph..

Outlook

Outlook customer threads flow into the context graph with full identity resolution across the org..

Calendar

Google Calendar

Meetings, attendees, and titles become part of the relationship signal — so AI knows who actually engaged, not just who was emailed..

Calendar

Outlook Calendar

Microsoft 365 calendar events and attendees join the relationship graph alongside email, calls, and CRM..

Messaging

Slack

Customer-channel and deal-room conversations become first-class context — without the model crawling Slack on every query..

MessagingRoadmap

Microsoft Teams

Teams channels and customer chats — on the roadmap based on customer demand..

Support

Pylon

Support conversations and ticket signal join the graph alongside CRM and calls — so AI sees the full customer health picture..

SupportRoadmap

Intercom

Intercom conversations and ticket data — on the roadmap based on customer demand..

SupportRoadmap

Zendesk

Zendesk tickets and customer support history — on the roadmap based on customer demand..

Project & tickets

Project & ticketsBeta

Linear

Engineering work tied to customer commitments — flowing into the graph so AI can tell you when a feature a deal hinges on actually ships..

Knowledge & docs

Knowledge & docsRoadmap

Notion

Internal docs, playbooks, and customer notes — on the roadmap based on customer demand..

Data warehouse

Data warehouseRoadmap

Snowflake

Write the context graph back to your warehouse so analytics, BI, and downstream pipelines run from the same resolved customer model..

Status

Live: Generally available. Used in production by Clearskies customers today.
Beta: Available to customers on request. We’re still hardening edges.
Roadmap: Not yet built. Tell us you need it — most integrations ship within weeks of a customer asking.

Frequently asked

MCP, in plain answers.

What is an MCP server?

An MCP server is a connector that exposes a system — a CRM, a call-recording tool, an email inbox — to AI clients through the Model Context Protocol (MCP), the open standard Anthropic introduced for connecting AI to external data. Once a tool is reachable as an MCP server, any MCP-compatible AI — Claude, ChatGPT, Cursor, n8n, custom agents — can read from it (and sometimes write to it) without the user wiring it in manually.

What MCP servers does Clearskies provide?

Clearskies provides one MCP endpoint that exposes a unified customer context graph built from every connected system. Today the live integrations behind that endpoint are Salesforce, HubSpot, Gong, Scratchpad, Fathom, Gmail, Outlook, Google Calendar, Outlook Calendar, Slack, and Pylon. Linear is in beta. Roadmap: Attio, Fireflies, Microsoft Teams, Intercom, Zendesk, Notion, Snowflake.

How is Clearskies different from a single-tool MCP server?

A single-tool MCP server gives AI access to one system in isolation. Clearskies resolves identity, timeline, and relationships across all connected systems before AI queries it — so a question like “what’s the status of the Acme deal?” returns a single coherent answer built from CRM, calls, email, and Slack, not five fragments the model has to stitch together. The benefit compounds: cheaper queries (one MCP call instead of five-to-fifteen), more consistent answers across runs, portable to every AI your team uses — Claude, ChatGPT, Cursor — and one endpoint to deploy and govern instead of per-tool connections in every user’s workspace.

What AI clients can connect to the Clearskies MCP server?

Any MCP-compatible client. Confirmed: Claude (desktop and web), ChatGPT (custom GPTs and agents), Cursor, n8n, Retool. The endpoint is standard MCP, so new clients work automatically as they adopt the protocol.

Not seeing your system?

Tell us what to connect next.

We add integrations based on real customer demand. If your system isn’t here yet, the fastest path is to tell us — most integrations ship within weeks of a customer asking.

Request an integration

Every connector covered. Every system in one graph.

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