Mio MCP. Automate calls, capture transcripts, and log data.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Mio bridges communication across Slack, Microsoft Teams, and Webex. This server lets your AI agent run automated phone calls—outbound prospecting, appointment confirmations, etc.—and capture all the data.
You get full transcripts, summaries, call logs, and real-time webhook notifications, so teams stay connected without switching apps or doing manual note-taking.
What your AI agents can do
Start ai call
Starts an outbound AI phone call using a specified script, voice, and target number.
Create webhook
Sets up a new external notification endpoint to receive event data from the server.
Delete webhook
Removes an existing, active webhook notification.
Start an outbound call using start_ai_call, set custom scripts, or stop a live interaction immediately with terminate_call.
Retrieve full text transcripts (get_call_transcript) and AI-generated summaries (get_call_summary) to understand call outcomes without reading notes.
Set up automated notifications by creating webhooks, allowing external systems to react instantly when a call status changes.
Check your current credit balance with get_credit_balance and list available voice options using list_available_voices.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Mio MCP Server: 12 Tools for Voice Automation
Manage the entire lifecycle of your voice interactions—from initiating a call to logging detailed outcomes—with these twelve tools.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Mio on Vinkius019dd125start ai call
Starts an outbound AI phone call using a specified script, voice, and target number.
019dd125create webhook
Sets up a new external notification endpoint to receive event data from the server.
019dd125delete webhook
Removes an existing, active webhook notification.
019dd125get account info
Retrieves basic user profile and account details for verification purposes.
019dd125get call details
Fetches specific information about a single call, including its status, duration, and outcome.
019dd125get credit balance
Checks your remaining credit balance to estimate how many calls you can still make.
019dd125get call summary
Generates an AI-powered summary from a completed call, extracting key insights and data points.
019dd125get call transcript
Retrieves the full text log of every thing said during a specific phone call.
019dd125list calls
Provides an overview by listing every recorded call log in your account history.
019dd125list available voices
Returns a list of all neural voices available for the AI agent, including gender and accent details.
019dd125list webhooks
Shows all currently active webhook notification endpoints configured on the server.
019dd125terminate call
Immediately stops an active or ongoing AI-powered phone conversation.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Mio, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,000+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mio. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 12 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Manually tracking call notes across Slack, Teams, and Webex is exhausting.
Every time a sales rep finishes a demo or a support agent solves an issue, they have to stop talking and manually copy the key outcomes—'Needs pricing review,' 'Confirming Tuesday 2 PM slot'—into a ticketing system. This is where notes get lost, details get missed, and data entry becomes a full-time job.
With Mio MCP Server, the call recording handles it all. After the conversation ends, your agent runs `get_call_summary`. You don't read minutes of transcript; you get structured, actionable insights—Outcome: Positive. Next Step: Price follow up. The data is ready to pipe directly into whatever system needs it.
Using the `get_call_transcript` tool gives you the entire conversation, not just bullet points.
Most systems only give you a 'summary,' which is fine for quick status checks. But sometimes, finding that single keyword or specific agreement requires seeing exactly what was said. You can't trust an AI to perfectly summarize the nuance of a conversation.
Using `get_call_transcript` gives your agent the raw, full text log—every word spoken by both parties. This is critical for legal compliance, deep sentiment analysis, or building advanced NLP pipelines that need 100% fidelity.
What you can do with this MCP connector
Mio lets your AI agent handle automated calls, connecting communication across Slack, Microsoft Teams, and Webex. This server runs full outbound prospecting calls and appointment confirmations while capturing all data points for you. You get transcripts, summaries, call logs, and real-time notifications—all without switching apps or doing manual note-taking.
Initiating and Managing Calls
You start an outbound AI phone conversation using start_ai_call. This function lets you specify a custom script, select the voice, and provide the target number. If something goes wrong or if you need to end the talk early, you can immediately stop the live interaction with terminate_call.
The agent needs credit to run these calls; check your remaining balance first using get_credit_balance.
Analyzing Call Data After the Fact
Once a call finishes, Mio doesn't just record it—it analyzes it for you. You can pull the full text log of everything said during that specific phone conversation with get_call_transcript. To save yourself from reading pages of text, get_call_summary generates an AI-powered summary that pulls out key insights and actionable data points right away.
For a deep dive into any past interaction, you can list every recorded call log using list_calls, then fetch specific details like the status, duration, or final outcome for one conversation with get_call_details.
System Setup and Voice Control
This server gives you full control over how it operates. You choose from a variety of neural voices—you can see all the available options, including gender and accent details, by calling list_available_voices. For system connectivity, you set up automated notifications using webhooks. You establish a new external notification endpoint with create_webhook, which lets other systems react instantly when a call status changes.
If that webhook isn't working anymore, you can wipe it clean using delete_webhook, and check all your active connections by running list_webhooks. To verify who you are before connecting anything else, you retrieve basic user profile and account details with get_account_info.
Workflow Summary
You run the calling process entirely through your AI client. Your agent uses tools like start_ai_call to initiate and manage the whole phone conversation lifecycle. You'll get full visibility into call performance, whether it's checking the account info via get_account_info, managing webhook endpoints using create_webhook, or simply reviewing old logs by calling list_calls.
It’s designed so your team stays connected without needing to jump between multiple applications.
019dd125-b8e0-70ab-9863-6820a56a4bed 
How Mio MCP Works
- 1 Subscribe to the Mio server and provide your API credentials.
- 2 Your AI client calls a tool like
start_ai_call, defining the target number, script, and voice. - 3 The system handles the call flow; you then use tools like
get_call_transcriptorget_call_summaryto retrieve the results.
The bottom line is: You tell your AI client what to say, it makes the call and captures all the resulting data for you.
Who Is Mio MCP For?
This setup is essential for Sales Development Reps (SDRs) who need high-volume outreach without sacrificing quality. It's also critical for Customer Service Managers running appointment confirmation campaigns, and developers building complex voice-first applications.
Uses start_ai_call repeatedly to automate cold prospecting calls, using the resulting data from get_call_summary to prioritize leads for manual follow-up.
Deploys AI voice agents via start_ai_call for tasks like appointment confirmation. They monitor success rates using list_calls and track missed calls using webhooks.
Builds call-logging microservices by integrating the server's webhook tools (create_webhook) to ensure that every state change (e.g., 'Ringing' -> 'Completed') triggers an action in another service.
What Changes When You Connect
- Instantly get full call records. Instead of manually writing notes after a demo, use
get_call_transcriptto feed the entire conversation text directly into your CRM or knowledge base. - Track performance without logging in. Configure webhooks using
create_webhook. Your internal dashboard gets hit with an alert the second a status changes—missed call, connected, etc. - Automate high-volume outreach. Use
start_ai_callto run hundreds of outbound calls following complex scripts, freeing up your SDRs for actual face-to-face interactions. - Understand outcomes faster than ever. Don't read 20 minutes of transcript; use
get_call_summary. It boils down the key takeaways and action items into a few bullet points. - Know your limits before you start. Before launching a campaign, run
get_credit_balanceto see exactly how many calls you can afford based on current usage.
Real-World Use Cases
The Sales Follow-Up Campaign
SDR needs to follow up with 50 leads. Instead of calling every single one, they use start_ai_call for an automated sequence. Once finished, the agent runs get_call_summary on all 50 results, instantly generating a list of 'Positive' and 'Needs Follow-up' outcomes to prioritize their day.
The Appointment Confirmation Loop
A CS team needs to confirm meetings for the week. They use start_ai_call with a specific script and voice selection. If the call results in a 'Negative' outcome, an adjacent service watches the webhook event (via create_webhook) and automatically sends a Slack message to the manager.
Auditing Call Scripts
A developer wants to see how often the AI agent is being terminated early. They list all logs using list_calls, then check get_call_details on specific entries to verify if the call ended normally or was manually stopped via terminate_call.
Building a Voice-First CRM Hook
A dev needs all voice interaction data in their database. They connect Mio and use webhooks (create_webhook) to listen for the 'Call Completed' event, which then triggers another service that pulls the full text log via get_call_transcript.
The Tradeoffs
Trying to manually track call outcomes
The user thinks they need to check every single Webex meeting link and copy/paste notes into a spreadsheet, spending hours doing it.
→
Stop copying. Use get_call_summary right after the call completes. This tool automatically extracts the outcome (Positive/Negative) and summarizes key decisions, giving you structured data instead of unstructured text.
Assuming all calls are available forever
The user tries to manually find a transcript from three months ago by searching through old emails or records.
→
Use the list_calls tool first. This gives you an index of every log entry. Then, use get_call_details with the specific call ID to access historical data like transcripts and summaries.
Ignoring system changes
A developer builds a workflow that depends on knowing when a call fails, but forgets to set up any monitoring.
→
Use create_webhook immediately after setting up the flow. This ensures that every status change—like 'Failed' or 'Disconnected'—sends an immediate event notification to your system.
When It Fits, When It Doesn't
You should use Mio if your core pain point is converting high-volume, cross-platform voice conversations into structured, actionable data. If you are primarily doing sales outreach or customer service confirmation at scale, this server automates the calling and the logging.
Don't use it if: 1) You just need to send a simple message (use basic messaging APIs instead). 2) Your communications never involve talking to a person on the phone. For pure chat automation, Mio is overkill. 3) You only care about manually scheduling things—use your standard calendar API.
Use start_ai_call when you need an AI agent to execute a script and record the outcome. Use get_call_transcript when compliance or deep keyword analysis requires the raw text. Stick to Mio if voice interaction is central to your business process.
Common Questions About Mio MCP
How do I start an AI call using the `start_ai_call` tool? +
You must provide three things: a target phone number, the specific script/instructions for the agent, and which voice you want to use. The agent handles dialing and conversation flow automatically.
What is the difference between `get_call_summary` and `get_call_transcript`? +
get_call_summary gives you a concise, readable summary of the outcome (e.g., 'Appointment confirmed'). get_call_transcript gives you the full text log—every word spoken during the call.
How do I set up notifications for when a call ends? +
You use the create_webhook tool. This establishes an event listener endpoint. When a call changes status (like 'Completed'), Mio sends a payload to your specified URL.
Can I check how much credit I have left with `get_credit_balance`? +
Yes, running get_credit_balance checks your current account funds. The output estimates remaining minutes based on your usage history and rates.
How do I stop an AI call mid-stream if it goes wrong? +
Use the terminate_call tool. This sends a signal to Mio that instantly ends the active conversation, allowing you to take over or re-route the process.
How do I use the `list_calls` tool to check my past call logs? +
The list_calls tool retrieves a high-level log of every recorded interaction. This list provides basic metadata, including the call status, total duration, and outcome for quick auditing. You can quickly scan dozens of calls without pulling full transcripts.
What does `list_available_voices` tell me about my AI voice options? +
This tool lists every neural voice available to your agent. For each option, you get critical details like the gender, accent, and specific language (e.g., Male/US English). This lets you match the AI's tone perfectly for your target market.
If I have a call ID, how is `get_call_details` different from just listing calls? +
list_calls gives you an overview of multiple interactions. In contrast, get_call_details pulls all the granular metadata for one specific call ID. This is what you use when you need deep information—like internal IDs or specific contact data—for downstream processing.
Can I start an automated AI phone call? +
Yes. Provide a phone number, instructions for the AI agent, and optionally select a voice. Mio will call and follow the script autonomously.
How does Mio authentication work? +
Mio requires an API Key sent via the X-API-Key header against api.mio.gg/api/v1.
Can I get transcripts and AI summaries? +
Yes. After a call completes, retrieve the full text transcript and an AI-generated summary with extracted data points.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.