tl;dv MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Get Api Status, Get Meeting Details, Get Meeting Duration, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add tl;dv as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The tl;dv app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 tl;dv. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in tl;dv?"
)
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 tl;dv MCP Server
Connect your tl;dv account to any AI agent and simplify how you manage your meeting recordings, transcripts, and AI-generated insights through natural conversation.
LlamaIndex agents combine tl;dv 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 Oversight — List all recorded meetings and retrieve detailed metadata, including participants and duration.
- Transcript Access — Fetch full transcriptions for any meeting to search for specific discussion points.
- AI Insights — Read AI-generated notes, summaries, and key moments (highlights) to quickly understand meeting outcomes.
- External Import — Programmatically import meeting recordings from external URLs for processing.
- Content Retrieval — Get direct download links for video recordings and access recent transcripts instantly.
- Operational Monitoring — Check API connectivity and account status directly from the agent.
The tl;dv 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.
All 12 tl;dv tools available for LlamaIndex
When LlamaIndex connects to tl;dv through Vinkius, your AI agent gets direct access to every tool listed below — spanning meeting-transcription, call-recording, summarization, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Check connection
Get meeting info
Check call length
Get key moments
Read AI summaries
List attendees
Read transcription
Get video file URL
Upload recording URL
List latest transcripts
List recent meetings
Verify credentials
Connect tl;dv to LlamaIndex via MCP
Follow these steps to wire tl;dv into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the tl;dv MCP Server
LlamaIndex provides unique advantages when paired with tl;dv through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine tl;dv tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain tl;dv tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query tl;dv, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what tl;dv tools were called, what data was returned, and how it influenced the final answer
tl;dv + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the tl;dv MCP Server delivers measurable value.
Hybrid search: combine tl;dv real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query tl;dv 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 tl;dv for fresh data
Analytical workflows: chain tl;dv queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for tl;dv in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with tl;dv immediately.
"List all my recorded meetings from this month."
"Summarize the key decisions made in the 'Q4 Roadmap Sync' meeting."
"Show me who attended the meeting with 'Alex' (ID: mtg_88231)."
Troubleshooting tl;dv MCP Server with LlamaIndex
Common issues when connecting tl;dv to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcptl;dv + LlamaIndex FAQ
Common questions about integrating tl;dv MCP Server with LlamaIndex.