Fathom 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 Fathom 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 Fathom. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Fathom?"
)
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 Fathom MCP Server
Connect your Fathom.video account to any AI agent and take full control of your meeting intelligence and automated note-taking through natural conversation.
LlamaIndex agents combine Fathom 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 Orchestration — List recent meetings and search across your entire recording history to retrieve titles, dates, and participant metadata natively
- AI Transcription — Retrieve full speaker-attributed transcripts with timestamps to review exact discussions and verbal commitments limitlessly
- Contextual Summarization — Get AI-generated summaries distilling key discussion points, decisions, and overall meeting context into a concise format
- Action Item Tracking — Extract AI-identified tasks with assigned owners and due dates to automate post-meeting follow-up workflows
- Recording Management — Access video and audio recording URLs for immediate streaming or download bypassing the web interface
- Attendee Auditing — List all meeting participants including join/leave times and speaking duration to verify engagement levels synchronously
- Team Intelligence — Access meetings shared with your Fathom team to monitor cross-functional discussions and organizational knowledge securely
- Highlight Navigation — Retrieve specific moments flagged as important during calls to focus on critical insights without reviewing entire recordings
The Fathom 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 Fathom to LlamaIndex via MCP
Follow these steps to integrate the Fathom 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 Fathom
Why Use LlamaIndex with the Fathom MCP Server
LlamaIndex provides unique advantages when paired with Fathom through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Fathom tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Fathom tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Fathom, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Fathom tools were called, what data was returned, and how it influenced the final answer
Fathom + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Fathom MCP Server delivers measurable value.
Hybrid search: combine Fathom real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Fathom 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 Fathom for fresh data
Analytical workflows: chain Fathom queries with LlamaIndex's data connectors to build multi-source analytical reports
Fathom MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Fathom to LlamaIndex via MCP:
get_action_items
Get AI-identified action items for a meeting
get_attendees
Get the list of participants for a meeting
get_highlights
Get important moments flagged in a meeting
get_me
Get current API token user profile
get_meeting
Get details for a specific Fathom meeting
get_recording
Get the recording URLs for a meeting
get_summary
Get the AI-generated summary for a meeting
get_team_meetings
List meetings shared with your team
get_transcript
Get the full transcript for a meeting
get_webhooks
List configured webhooks
list_meetings
List all Fathom meetings
search_meetings
Search for meetings by keyword
Example Prompts for Fathom in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Fathom immediately.
"Show me the summary and action items for my last meeting"
"Search my meetings for mentions of 'pricing strategy'"
"Get the transcript for meeting 'abc-123'"
Troubleshooting Fathom MCP Server with LlamaIndex
Common issues when connecting Fathom to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFathom + LlamaIndex FAQ
Common questions about integrating Fathom 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 Fathom 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 Fathom to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.