How do I get my Uniphore Access Token and Org ID?

Log in to your Uniphore account, navigate to Settings > API Access, and generate a new token. Your Organization ID is displayed in the same settings panel.

Can I get AI-generated summaries of meetings?

Yes! Use the get_meeting_summary tool with a meeting ID to retrieve the concise AI summary of that call.

Can I extract action items from a call?

Yes! Use the get_action_items tool with a meeting ID. Uniphore AI identifies next steps and assigns them to speakers if possible.

Can I search for specific topics in past meetings?

Yes! Use the search_meetings tool with relevant keywords or topic names to find matching recorded calls.

Uniphore Conversation AI MCP Server for LangChain 8 tools — connect in under 2 minutes

Name: Uniphore Conversation AI
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Uniphore Conversation AI through the 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({
        "uniphore-conversation-ai": {
            "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 Uniphore Conversation AI, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 Uniphore Conversation AI MCP Server

Connect Uniphore to any AI agent and unlock powerful conversation intelligence -- retrieve meeting transcripts, AI-generated summaries, action items, and analytics through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Uniphore Conversation AI through native MCP adapters. Connect 8 tools via the 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 Transcripts -- Get speaker-tagged transcripts of any recorded call or meeting
AI Summaries -- Retrieve concise summaries of key discussion points
Action Items -- Extract next steps and tasks identified during meetings
Conversation Analytics -- View talk ratios, sentiment, topics, and engagement metrics
Search Meetings -- Find past meetings by keyword or topic discussed

The Uniphore Conversation AI MCP Server exposes 8 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 Uniphore Conversation AI to LangChain via MCP

Follow these steps to integrate the Uniphore Conversation AI 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 8 tools from Uniphore Conversation AI via MCP

Why Use LangChain with the Uniphore Conversation AI MCP Server

LangChain provides unique advantages when paired with Uniphore Conversation AI through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents — combine Uniphore Conversation AI 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 Uniphore Conversation AI queries for multi-turn workflows

Uniphore Conversation AI + LangChain Use Cases

Practical scenarios where LangChain combined with the Uniphore Conversation AI MCP Server delivers measurable value.

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

Autonomous research agents: LangChain agents query Uniphore Conversation AI, synthesize findings, and generate comprehensive research reports

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

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

Uniphore Conversation AI MCP Tools for LangChain (8)

These 8 tools become available when you connect Uniphore Conversation AI to LangChain via MCP:

get_action_items

Get action items extracted from a meeting

get_meeting

Get details of a specific meeting

get_meeting_analytics

Get conversation analytics and insights for a meeting

get_meeting_summary

Get the AI-generated summary of a meeting

get_transcript

Get the full transcript of a meeting

list_meetings

Use this to discover meeting IDs before querying specific details. List all recorded meetings and calls

list_topics

List all tracked topics and keywords in the organization

search_meetings

Search meetings by keyword or topic

Example Prompts for Uniphore Conversation AI in LangChain

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

"Show me the summary for meeting MTG-123."

"Get the transcript for meeting MTG-456."

"What are the action items from the last sales call?"

Troubleshooting Uniphore Conversation AI MCP Server with LangChain

Common issues when connecting Uniphore Conversation AI to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Uniphore Conversation AI + LangChain FAQ

Common questions about integrating Uniphore Conversation AI 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.