Granola MCP

CALL ANY TOOL

List notes, get summaries, search transcripts, and retrieve action items via Granola's MCP server.

granolamcp_list_meetings

List meetings

List the user's Granola meeting notes within a time range. Returns meeting titles and metadata. IMPORTANT: For short-term questions about recent meeting details, prefer using query_granola_meetings instead. When to use: - User asks to list their meetings - User asks about action items, decisions, or summaries from meetings over a longer or specific date range - User asks about content from their meeting transcripts - User references 'Granola notes' or 'meeting notes' or 'transcripts' When NOT to use: - User is asking about upcoming calendar events or scheduling - User wants to create/modify calendar invites Filtering: - Omit workspace_only and involvement to return every meeting the user is allowed to access - For 'my meetings' or meetings the user was involved in, set both involvement conditions to true; true conditions combine using OR - Set captured_by_me to true for meetings whose Granola notes the user captured, or false to exclude them - Set listed_as_participant to true for meetings where the user is a known participant, or false to exclude them - False involvement conditions are exclusions and combine with the positive conditions using AND; omit a condition to ignore it - For Team Space or public workspace meetings, set workspace_only to true - workspace_only and involvement combine using AND Use get_meetings to retrieve detailed meeting content after identifying relevant meetings. Use list_meeting_folders to discover folder IDs, then pass a folder_id to list meetings within a specific folder.

Parameters

Name

Type

Required

Description

involvement

object

Optional

Optional involvement filter. Conditions set to true form an OR inclusion group. Conditions set to false are exclusions applied using AND. Omitted conditions are ignored.

schema_version

string

Optional

Optional schema version to use for tool execution

time_range

string

Optional

Time range to query meetings from

tool_version

string

Optional

Optional tool version to use for tool execution

workspace_only

boolean

Optional

Set to true only when the user explicitly asks for Team Space, public workspace, or workspace-visible meetings. Omit to search every meeting the user is allowed to access.

granolamcp_get_meetings

Get meetings

granolamcp_list_meeting_folders

List meeting folders

granolamcp_get_account_info

Get account info

granolamcp_query_granola_meetings

Query granola meetings

granolamcp_get_meeting_transcript

Get meeting transcript

Build your Agent

Drop the toolkit in, point it at the user, and your meeting intelligence agent can use Granola MCP from the first run.

import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { z } from "zod";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["granolamcp"], toolNames: ["granolamcp_notes_list", "granolamcp_note_get", "granolamcp_note_summary"] },
  pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  schema: z.object({}).passthrough(),
  func: async (args) => {
    const { data } = await sk.tools.executeTool({
      toolName: t.tool.definition.name,
      identifier: "user_123",
      params: args,
    });
    return JSON.stringify(data);
  },
}));

const agent = createReactAgent({ llm, tools: lcTools });

import { ScalekitClient } from "@scalekit-sdk/node";
import OpenAI from "openai";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["granolamcp"], toolNames: ["granolamcp_notes_list", "granolamcp_note_get", "granolamcp_note_summary"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  type: "function",
  function: {
    name: t.tool.definition.name,
    description: t.tool.definition.description,
    parameters: t.tool.definition.input_schema,
  },
}));

const resp = await openai.responses.create({
  model: "gpt-4o", input: prompt, tools: llmTools,
});

import { ScalekitClient } from "@scalekit-sdk/node";
import Anthropic from "@anthropic-ai/sdk";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["granolamcp"], toolNames: ["granolamcp_notes_list", "granolamcp_note_get", "granolamcp_note_summary"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
  model: "claude-sonnet-4-6", max_tokens: 1024,
  tools: llmTools,
  messages: [{ role: "user", content: prompt }],
});

import { Agent } from "@google/adk/agents";
import {
  MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
  connectionParams: new StreamableHTTPConnectionParams({
    url: "https://mcp.scalekit.com/granolamcp",
    headers: { Authorization: `Bearer ${userScopedToken}` },
  }),
});

const agent = new Agent({
  name: "agent", model: "gemini-2.0-flash",
  tools: await toolset.getTools(),
});

Try these prompts

Paste any prompt into your agent to start using Granola MCP.

Search & recall

Copy the prompt

Copied

List all meeting notes from this week.

Copy the prompt

Copied

Search notes for [topic].

Copy the prompt

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Get the summary of [meeting name].

Copy the prompt

Copied

Find notes with [person name] as attendee.

Action & follow-up

Copy the prompt

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Get action items from [meeting name].

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List all open action items this week.

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Who attended [meeting name]?

Copy the prompt

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Find notes where [decision] was made.

Reporting

Copy the prompt

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Summarize all customer calls this month.

Copy the prompt

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Which meetings had no action items?

Copy the prompt

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List notes from [account name] this quarter.

Copy the prompt

Copied

Find meetings that ran over 60 minutes.

SEE HOW AUTH WORKS

Users authorize Granola MCP once. Their credentials stay vaulted, every call is checked, and every action is logged.

1

Authorize

Your user connects

Granola MCP

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

2

Store

Their

Granola MCP

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

3

Resolve

When your agent calls a

Granola MCP

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

4

Audit

Every

Granola MCP

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

Same per-user auth pattern across other meeting intelligence agents and MCP connectors. Working code, live demos, fork what fits.

GTM and RevOps Teams

CRM AI agent

Reads the Granola transcript after every call, extracts next steps and updates the HubSpot record, drafts the follow-up in Gmail, and confirms in Slack, all on the rep's own delegated OAuth.

GTM and RevOps Teams

Sales call prep agent

Reads tomorrow's calls from Google Calendar, mines past Granola notes and Attio history for context, and delivers each rep a prep brief in Slack, scoped to the calls that rep actually owns.

GTM and RevOps Teams

Competitive intelligence briefing agent

Scans Gong calls for competitor mentions, matches each one to its Notion battlecard, and DMs every affected rep a single Slack digest per cycle. Every call runs as the PMM who owns the briefing, never a shared bot.

GTM and RevOps Teams

Outbound prospecting agent

Searches Apollo for prospects matching your ICP, scores and ranks them, drafts personalized outreach in Gmail, and logs every send to Google Sheets. Mail goes out as the rep, not from a shared inbox.

Test other agents

Same per-user auth pattern across other meeting intelligence agents and MCP connectors. Working code, live demos, fork what fits.

GTM

CRM AI agent

Turn each Granola call transcript into a HubSpot record update, a drafted Gmail follow-up, and a Slack recap.

SALES

Sales call prep agent

Read tomorrow's calls from Google Calendar, mine Granola notes and Attio history, and deliver each rep a prep brief in Slack.

GTM

Competitive intelligence briefing agent

Scan Gong calls for competitor mentions, match each one to its Notion battlecard, and DM every affected rep a single Slack digest.

SALES

Outbound prospecting agent

Search Apollo for ICP matches, rank them, draft personalised Gmail outreach, and log every send to Google Sheets.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

01.

Shared tokens break per-user analytics

A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential so attribution, audit, and scope stay accurate.

// shared token
 audit → bot_service_account
 user_filter → broken

 // scalekit
 audit → user_abc
 scope → enforced ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

Granola MCP today. Others tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access Granola MCP as the user or as a shared key?

As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the Granola MCP bearer token stored?

In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in Granola MCP?

Yes. Pass a tool name filter to listScopedTools so the meeting intelligence agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Granola MCP.

What happens when a user revokes Granola MCP access?

The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Does this connector access the same workspace as the Granola connector?

Yes. Both connect to the same Granola workspace via the user's token. The authorizing user's scope determines which notes are accessible. There is no difference in data access between the two connector types.

Tools your meeting intelligence agent reaches for on Granola MCP, scoped per user.