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 CrewAI 8 tools — connect in under 2 minutes

Name: Uniphore Conversation AI
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Uniphore Conversation AI through Vinkius, pass the Edge URL in the `mcps` parameter and every Uniphore Conversation AI tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Uniphore Conversation AI Specialist",
    goal="Help users interact with Uniphore Conversation AI effectively",
    backstory=(
        "You are an expert at leveraging Uniphore Conversation AI tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Uniphore Conversation AI "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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.

When paired with CrewAI, Uniphore Conversation AI becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Uniphore Conversation AI tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Uniphore Conversation AI MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 8 tools from Uniphore Conversation AI

Why Use CrewAI with the Uniphore Conversation AI MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Uniphore Conversation AI through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Uniphore Conversation AI + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Uniphore Conversation AI for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Uniphore Conversation AI, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Uniphore Conversation AI tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Uniphore Conversation AI against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Uniphore Conversation AI MCP Tools for CrewAI (8)

These 8 tools become available when you connect Uniphore Conversation AI to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Uniphore Conversation AI + CrewAI FAQ

Common questions about integrating Uniphore Conversation AI MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.