Your Meetings, Notes, and Relationships — Now Accessible in Claude, ChatGPT, and More

Your Data Shouldn't Be Trapped in One App

Here's a pattern most of us are familiar with: you capture valuable data in one tool, then spend your time copying it between others. Your meeting notes live in one place. Your AI assistant lives in another. When you want to ask Claude about a meeting you had last Tuesday, you end up pasting the transcript into the chat. When you want ChatGPT to draft a follow-up email, you copy the summary and the attendee list. When you want Gemini to help you prep for tomorrow's meetings, you manually describe your calendar.

All that copying defeats the purpose of having a structured knowledge graph in the first place. Your data should flow to the tools where you need it — automatically, securely, and without you playing intermediary.

That's exactly what Grafite's MCP integration does.

What Is MCP (and Why Should You Care)?

The Model Context Protocol — MCP — is an open standard that lets AI tools connect to external data sources securely. Think of it as a universal adapter between your data and any AI assistant that supports the protocol. Instead of manually feeding context to your AI, the AI connects directly to Grafite and pulls what it needs.

The practical result: when you're working in Claude, ChatGPT, Gemini, Cursor, or any other MCP-compatible tool, you can ask questions about your meetings, pull up notes, search across your people directory, and reference your task list — without leaving the tool you're already using and without copying a single thing.

It's your data, available wherever you think. That's the idea.

What's Actually Available Through MCP

When you connect Grafite via MCP, the AI tool gets read-only access to your professional knowledge graph. Here's what that includes:

Notes & Meetings

• Search across all your notes by keyword, date, or topic
• Pull up the full content of any note
• Get AI-generated meeting summaries
• Access complete meeting transcripts with timestamps

Calendar & Events

• List upcoming and past calendar events
• Get event details including attendees and meeting links

People & Companies

• Search your people directory by name, company, or role
• Get detailed person profiles with full meeting history
• See relationship context — when you last met, how often you connect

Tasks & Action Items

• List tasks by status, priority, or due date
• Search across tasks for specific action items
• View your task lists and boards

Cross-Entity Search

• Search across everything at once — notes, people, tasks, events
• The AI can combine data from multiple sources to answer complex questions

Ask Grafi

• The full Ask Grafi pipeline is available as a tool, meaning the AI assistant you're using can leverage Grafi's multi-step reasoning — searching across your notes, people, and meetings to assemble cited answers

That last one is worth pausing on. When you use Ask Grafi through MCP in Claude, for example, Claude can call Grafi as a tool mid-conversation. It doesn't just search your notes — it runs the same intelligent query planning and citation pipeline that powers Ask Grafi in the Grafite app. The result is deeply contextual answers with references back to specific meetings and notes.

Setting It Up: Genuinely 30 Seconds

We're not exaggerating about the setup time. Here's the whole process:

1. Open Settings → Connections in Grafite
2. Copy your MCP server URL: https://grafite.io/mcp
3. Add it to your AI tool's MCP configuration
4. Authenticate with your Grafite account when prompted

That's it. The connection uses OAuth, so your credentials are never shared with the AI tool directly. You authorize access once, and it stays connected until you revoke it.

Here's what the configuration looks like for the most popular tools:

Claude Desktop — Add to your MCP settings:

{
  "mcpServers": {
    "grafite": {
      "url": "https://grafite.io/mcp"
    }
  }
}

ChatGPT and Gemini follow similar patterns — Grafite's Settings page includes step-by-step guides for each supported client.

Once connected, the AI tool automatically discovers what data is available and can pull it in as needed during your conversations.

What You Can Actually Do With This

The tools are interesting, but what matters is what people actually do with them. Here are real use cases we've been exploring — and we think you'll find even more once you start experimenting.

Generate Polished Documents From Raw Meeting Data

Had a strategy session last week? Instead of writing the recap from memory, ask Claude: "Based on my strategy meeting from last Tuesday, draft an executive summary with the key decisions and next steps." Claude pulls the transcript and summary from Grafite, understands the context, and produces a polished document in seconds.

This works for client proposals, project briefs, status reports — anything that starts with "what happened in that meeting" and ends with a document someone else needs to read.

Prep for Meetings With Deep Context

Before a big client call, ask your AI: "Give me a briefing on everything I've discussed with Acme Corp over the past three months." The AI searches your people directory, pulls up every meeting with Acme contacts, and synthesizes the key themes, open items, and recent decisions into a concise briefing.

This is meeting prep without the homework. The data already exists in your knowledge graph — the AI just packages it.

Build Charts, Reports, and Visualizations

If you're using a tool like Claude that supports artifacts, you can ask it to analyze your meeting data and produce visual outputs. "Show me how many meetings I've had per week over the past quarter." "Create a chart of which companies I've met with most frequently." "Build a table of all open action items from my 1:1 meetings."

Your meeting data becomes something you can visualize and present — without exporting CSVs or building reports manually.

Cross-Reference and Pattern Recognition

"What topics keep coming up across my meetings with the engineering team?" or "Are there any action items from the past month that haven't been completed?" These are the kinds of questions that are nearly impossible to answer by reading through individual notes, but trivial for an AI with access to your full knowledge graph.

Over time, this gets more powerful. The more meetings you record and the richer your people directory becomes, the more patterns the AI can surface.

Draft Communications Based on Meeting Outcomes

"Draft a follow-up email to the attendees of my client meeting yesterday, summarizing the key decisions and asking them to confirm the next steps." The AI pulls the meeting summary, identifies the attendees from your people directory, and writes a ready-to-send email with the right tone and detail level.

This also works for Slack messages, project updates, weekly reports, and any other communication that originates from a meeting.

Industry-Specific Use Cases

If You're a Project Manager

Your meetings generate decisions, dependencies, and commitments across multiple teams and workstreams. Connect Grafite to Claude and you can:

• Ask "What decisions were made across all my meetings this week?" and get a consolidated list with citations
• Generate weekly status reports from your meeting summaries automatically
• Create risk logs by asking "What concerns or blockers were raised in my project meetings this month?"
• Draft stakeholder updates that pull directly from meeting transcripts — not from your memory of what was said

If You're in Sales

Every client conversation is a data point. With MCP access, your AI can:

• Build account briefings before calls: "Summarize my relationship history with this prospect, including all meetings, decisions, and open questions"
• Draft personalized follow-up emails using the actual content of the conversation — not generic templates
• Track commitment history: "What has this client committed to across our conversations?" with dates and citations
• Identify cross-sell opportunities by asking "What pain points has this account mentioned that we haven't addressed?"

If You're an Executive

Your calendar is packed and your context-switching is constant. MCP makes your meeting data work harder:

• Generate board-ready summaries from weeks of meetings: "Synthesize the key themes, risks, and decisions from my leadership meetings this quarter"
• Prep for investor or board meetings with data-backed briefings pulled from your actual conversations
• Ask "What are the top three unresolved issues across my direct reports' 1:1s this month?" and get a cited answer
• Draft strategic memos that reference specific meetings and decisions, not vague recollections

If You're a Consultant or Freelancer

You work across multiple clients and need to keep each relationship distinct. MCP helps you:

• Quickly context-switch between clients: "Brief me on my Acme account before this afternoon's call"
• Generate deliverables from meeting data: "Based on my discovery meetings with this client, draft a project scope document"
• Track billable time by asking "How many meetings have I had with each client this month?"
• Build case studies by synthesizing meeting outcomes across an entire engagement

Security and Privacy

We take this seriously, so here's how it works:

OAuth 2.1 authentication. Your Grafite credentials are never shared with the AI tool. You authorize access through a standard OAuth consent flow — the same approach used by every major platform.

Read-only access. MCP tools can read your data but can't modify it. Nothing gets created, updated, or deleted through the MCP connection.

Per-user isolation. The AI only accesses your data — scoped to your account via Supabase Row Level Security. There's no way to access another user's data through the MCP connection.

Revocable anytime. If you want to disconnect, go to Settings → Connections and revoke access. The AI tool immediately loses access to your data.

No data retention by Grafite. The MCP connection is stateless. Grafite doesn't log the queries made through MCP or retain any session data beyond what's needed to authenticate the request.

What the AI tool does with the data once it receives it depends on that tool's privacy policy — so be sure you're comfortable with the AI provider you're connecting to. But on Grafite's side, the connection is as locked down as we can make it.

"But Grafite Already Has Ask Grafi"

True — and Ask Grafi isn't going anywhere. It's still the fastest way to ask questions about your meeting data directly inside Grafite, and it works without any setup.

MCP is about extensibility. It's for when you're already working in Claude and want to reference a meeting without switching tabs. It's for when you want ChatGPT to draft a document that pulls from your actual meeting data. It's for when you're coding in Cursor and need to check what was decided in a meeting about the feature you're implementing.

Think of Ask Grafi as the built-in brain and MCP as the open door. We built Ask Grafi because your data should be askable. We built MCP because your data should also be portable — available in whatever tool you're using at the moment, not locked into ours.

What's Next

This is the first version of our MCP integration, and we're actively expanding it. On the roadmap:

• Write operations — create notes, add tasks, and update records from external AI tools
• Additional prompts — pre-built prompt templates for common workflows (weekly recap, meeting prep, action item review)
• Deeper tool integrations — richer data formats and more granular search capabilities

The architecture is designed to grow. Every new feature we add to Grafite — every new data type, every new relationship, every new capability — automatically becomes available through MCP to every connected tool.

Get Connected

If you're already using Grafite, head to Settings → Connections to set up MCP. It takes 30 seconds and your meeting data is immediately available in Claude, ChatGPT, Gemini, Cursor, and any other MCP-compatible tool.

If you haven't tried Grafite yet, sign up free — everything is free during beta, including MCP access. Start recording meetings, build your knowledge graph, and then connect it to the AI tools you already use. Your data, your tools, no walls between them.