Fireflies.ai 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 Fireflies.ai as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 Fireflies.ai. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Fireflies.ai?"
)
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 Fireflies.ai MCP Server
Connect your Fireflies.ai account to any AI agent and unlock the power of meeting intelligence through the Model Context Protocol (MCP). Fireflies.ai automates your meeting notes, transcribes conversations across several platforms, and provides deep analytics to help your team stay aligned. Now, you can query your entire meeting history and manage your transcription bot directly through natural conversation.
LlamaIndex agents combine Fireflies.ai tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through the 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
- Transcript Retrieval — List recent meetings and fetch detailed summaries, action items, and keywords from any transcript.
- AskFred Integration — Leverage Fireflies' AI assistant (AskFred) to ask questions about your meetings or start new analysis threads.
- Live Bot Control — Invite the Fireflies bot to ongoing meetings (Zoom, Google Meet, etc.) by simply providing the meeting URL.
- Conversation Analytics — Access aggregate metrics like talk-to-listen ratios and words-per-minute to improve team communication.
- User & Team Management — List team members and fetch user-specific meeting metadata.
- Transcript Management — Rename transcripts or delete them to keep your meeting database organized and up to date.
- Real-time Monitoring — See which meetings are currently being recorded and transcribed in real-time.
The Fireflies.ai 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 Fireflies.ai to LlamaIndex via MCP
Follow these steps to integrate the Fireflies.ai 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 Fireflies.ai
Why Use LlamaIndex with the Fireflies.ai MCP Server
LlamaIndex provides unique advantages when paired with Fireflies.ai through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Fireflies.ai tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Fireflies.ai tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Fireflies.ai, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Fireflies.ai tools were called, what data was returned, and how it influenced the final answer
Fireflies.ai + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Fireflies.ai MCP Server delivers measurable value.
Hybrid search: combine Fireflies.ai real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Fireflies.ai 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 Fireflies.ai for fresh data
Analytical workflows: chain Fireflies.ai queries with LlamaIndex's data connectors to build multi-source analytical reports
Fireflies.ai MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Fireflies.ai to LlamaIndex via MCP:
add_to_live_meeting
Invite Fireflies to a live meeting
create_ask_fred_thread
Ask a question to AskFred
delete_transcript
Delete a transcript
get_analytics
Get meeting analytics
get_ask_fred_thread
Get AskFred thread messages
get_transcript
Get transcript details
get_user
Get user details
list_active_meetings
List meetings currently being recorded
list_ask_fred_threads
List AskFred threads
list_transcripts
List recent transcripts
list_users
List team users
update_meeting_title
Rename a meeting
Example Prompts for Fireflies.ai in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Fireflies.ai immediately.
"List my 5 most recent meeting transcripts."
"Invite Fireflies to join my current meeting at https://zoom.us/j/123456789"
"Show me the action items from meeting ID 'trans_987'."
Troubleshooting Fireflies.ai MCP Server with LlamaIndex
Common issues when connecting Fireflies.ai to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFireflies.ai + LlamaIndex FAQ
Common questions about integrating Fireflies.ai 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 Fireflies.ai 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 Fireflies.ai to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.