Can my agent retrieve the AI summary of a specific Granola meeting?

Yes. Use the 'get_summary' tool. The agent will fetch the native generative results, reducing the bulk meeting content into synthesized blocks and key takeaways flawlessly.

How do I extract action items from recorded notes via chat?

Use the 'get_action_items' tool. Your agent will isolate targeted steps inferred from the meeting intent, enabling you to automate your post-meeting follow-up workflows natively.

Can I search for meetings from a specific date range through the agent?

Absolutely. Use the 'list_by_date' tool. Provide the start and end dates in ISO 8601 format. The agent will trigger temporal scoping routines to expose specific documents mapped historically.

Granola MCP Server for LangChain 12 tools — connect in under 2 minutes

Name: Granola
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Granola through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "granola": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Granola, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Granola MCP Server

Connect your Granola.ai account to any AI agent and take full control of your AI-powered meeting notes, searchable conversation memory, and automated summaries through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Granola through native MCP adapters. Connect 12 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Meeting Document Orchestration — List all meeting documents in your workspace and retrieve primary entry points for workspace interactions natively
Live Content Retrieval — Access full structured content of meeting documents, parsing human-modified annotations and ML-generated notes flawlessy
AI Summarization — Retrieve synthesized AI-generated blocks reducing bulk meeting content into concise overviews and key takeaway nodes limitlessly
Action Item Tracking — Isolate specifically categorized target steps inferred from recorded meeting intent to automate post-meeting follow-ups
Transcript Auditing — Retrieve full speaker-detected transcripts parsed locally on device, containing semantic and chronological speech metadata natively
Participant Navigation — Identify meeting attendees by cross-referencing calendar arrays bound to Granola sessions synchronously
Global Workspace Search — Execute full-text term detection across all documents to find specific discussions and prioritized ranked datasets
Folder & List Management — Enumerate high-level categorization labels grouping documents physically inside directories to browse your workspace hierarchy
Batch Retrieval Oversight — Fetch multiple meeting documents by their IDs in a single request to analyze complex cross-meeting dependencies securely

The Granola MCP Server exposes 12 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Granola to LangChain via MCP

Follow these steps to integrate the Granola MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 12 tools from Granola via MCP

Why Use LangChain with the Granola MCP Server

LangChain provides unique advantages when paired with Granola through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Granola MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Granola queries for multi-turn workflows

Granola + LangChain Use Cases

Practical scenarios where LangChain combined with the Granola MCP Server delivers measurable value.

RAG with live data: combine Granola tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Granola, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Granola tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Granola tool call, measure latency, and optimize your agent's performance

Granola MCP Tools for LangChain (12)

These 12 tools become available when you connect Granola to LangChain via MCP:

get_action_items

Extract action items identified from a meeting document

get_content

Retrieve the full structured content of a meeting document

get_documents_batch

Fetch multiple documents by their IDs in a single request

get_metadata

Retrieve metadata for a specific meeting document

get_participants

Retrieve the list of participants for a specific meeting

get_summary

Retrieve the AI-generated summary of a meeting document

get_transcript

Retrieve the full transcript of a meeting with speaker detection

list_by_date

List meeting documents within a specific date range

list_documents

List all meeting documents in the Granola workspace with pagination

list_folders

List all document lists (folders) in the Granola workspace

list_recent

List the 20 most recent meeting documents

search_documents

Full-text search across all meeting documents

Example Prompts for Granola in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Granola immediately.

"Show me the 5 most recent meeting documents"

"What were the action items from meeting 'abc-123'?"

"Search for meeting notes mentioning 'competitor analysis'"

Troubleshooting Granola MCP Server with LangChain

Common issues when connecting Granola to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Granola + LangChain FAQ

Common questions about integrating Granola MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.