Granola MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Granola as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Granola. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Granola?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine Granola tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Granola MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 12 tools from Granola
Why Use LlamaIndex with the Granola MCP Server
LlamaIndex provides unique advantages when paired with Granola through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Granola tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Granola tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Granola, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Granola tools were called, what data was returned, and how it influenced the final answer
Granola + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Granola MCP Server delivers measurable value.
Hybrid search: combine Granola real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Granola to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Granola for fresh data
Analytical workflows: chain Granola queries with LlamaIndex's data connectors to build multi-source analytical reports
Granola MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Granola to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Granola to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGranola + LlamaIndex FAQ
Common questions about integrating Granola MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Granola with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Granola to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.