SleekFlow MCP. Manage all chats (WhatsApp, Insta) from one API.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
SleekFlow connects your AI agent directly into WhatsApp, Instagram, Telegram, and WeChat. It lets you read real-time chat histories, check customer profiles, and send replies from a single terminal view.
Stop switching apps; manage every conversation—from initial lead to final resolution—wherever it happens.
What your AI agents can do
Get contact details
Fetches all metadata for a specific contact ID, giving you deep profile information.
List automation flows
Lists every configured workflow or chatbot tree currently running in the system.
List channels
Retrieves a list of all active and connected communication channels (e.g., WhatsApp, Instagram).
Use list_conversations to pull chat logs from every connected channel (WhatsApp, Instagram, etc.) into your agent's context.
The send_message tool lets your agent compose and dispatch a reply into an active conversation thread using the required chat ID and message body.
Use get_contact_details to fetch all metadata for a single customer, including their CRM ties and history.
The list_channels tool shows you every communication platform (e.g., WhatsApp Business, Instagram) currently connected to the server.
You can use list_contact_labels to see all pre-defined labels (like 'Hot Lead' or 'VIP Support') used to segment your customer base.
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Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
SleekFlow: 7 Tools for Omnichannel Communication
Use these tools to list channels, retrieve contact metadata, read conversation histories across platforms, and dispatch messages directly via your AI client.
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 SleekFlow on Vinkius019d7609get contact details
Fetches all metadata for a specific contact ID, giving you deep profile information.
019d7609list automation flows
Lists every configured workflow or chatbot tree currently running in the system.
019d7609list channels
Retrieves a list of all active and connected communication channels (e.g., WhatsApp, Instagram).
019d7609list contact labels
Lists every categorization label applied to contacts, helping you segment your user base.
019d7609list contacts
Retrieves a full list of all synchronized contacts managed by SleekFlow.
019d7609list conversations
Lists all ongoing chat threads across every connected channel, providing IDs needed for subsequent actions.
019d7609send message
Sends a drafted message to a specific conversation ID on an active channel.
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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
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Start with SleekFlow, then connect any of our 4,900+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,900+ others, all in one place
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- Works with Claude, ChatGPT, Cursor, and more
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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by SleekFlow. 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.
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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 7 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Managing customer conversations shouldn't require jumping between five different apps.
Right now, answering a single customer query means logging into WhatsApp Web, pulling up the chat history; switching to your CRM to check their labels; maybe opening Facebook Business Manager for follow-up. You spend more time navigating tabs and copying IDs than actually helping the customer.
With this MCP server, all those actions collapse into one API call sequence. Your agent uses `list_conversations` to gather the history, reads the context, cross-references it with labels via `get_contact_details`, and drafts a reply—all before you even lift your finger.
SleekFlow MCP Server: Send messages directly from your agent.
You no longer have to copy the customer's ID, navigate back to the correct chat thread, and manually hit 'Send.' The system handles all that plumbing for you.
Now, when your AI client determines a response is needed, it executes `send_message`, targeting the specific conversation ID. It’s direct. It works.
What you can do with this MCP connector
Yo. Listen up. If your customer conversations are spread out across WhatsApp, Instagram DMs, Telegram, and WeChat, you've got a mess on your hands. This server connects your AI agent directly into all those channels so you can stop switching apps. You manage every single lead—from the first sketchy message to the final resolution—right from one terminal view.
Reading Every Conversation. When you pull in chat logs, you're running list_conversations. This tool pulls real-time threads from every connected channel and feeds them straight into your agent's context. You don't just see a list of chats; you get the full conversation history for all ongoing threads across platforms like WhatsApp and Instagram.
The agent reads it all, so you know exactly what’s been said.
Sending Replies, Period. Once the agent knows what to say, it hits send_message. This tool lets your AI client compose and dispatch a reply directly into an active conversation thread. You don't copy-paste anything; the message goes out immediately using the required chat ID and body. It keeps the whole interaction centralized.
Deep Dive on Contacts. You need to know who you’re talking to, right? First, you run list_contacts to get a full roster of every synchronized user managed by SleekFlow. But that's just names. To really figure out what they are, the agent uses get_contact_details. This fetches deep metadata for any single customer—think CRM ties and their whole history.
It’s way more than just an email address.
To keep tabs on who needs attention, you run list_contact_labels. This shows all the pre-defined labels—like 'Hot Lead' or 'VIP Support'—so your agent can instantly segment your customer base and prioritize responses. You've got the full picture of their status right there.
System Oversight. Need to know what channels are even talking to us? Use list_channels. It spits out every single communication platform, like WhatsApp Business or Instagram, that’s currently connected to the server. If something looks weird, you check this list. You can also run list_automation_flows to see every chatbot tree or workflow that's running in the system—you know what your bots are doing at all times.
This setup lets your agent call these tools sequentially: it grabs the conversations with list_conversations, pulls the contact info using get_contact_details, and then fires off a response via send_message—all without you ever leaving the terminal. It’s clean, direct, and keeps everything centralized.
019d7609-4acc-70f0-b22d-8f8713c8c5e7 
How SleekFlow MCP Works
- 1 Subscribe to the SleekFlow server and provide your API key.
- 2 Your AI client calls
list_channelsfirst. This confirms which platforms are connected for action. - 3 The agent then uses tools like
list_conversationsorget_contact_detailsto gather necessary context before executing a final command, such as callingsend_message.
The bottom line is that your AI client treats every chat channel—WhatsApp, Telegram, Instagram—as one single, unified inbox accessed via structured tool calls.
Who Is SleekFlow MCP For?
Sales Development Reps (SDRs) and Support Managers need this. They're the people who get frustrated having to jump between WhatsApp Web, Zendesk, and their CRM just to answer one customer question. This server brings all those communication threads into a single API endpoint.
Reads a complex support thread from WeChat using list_conversations, drafts a personalized resolution, and sends it back immediately via send_message.
Uses the agent to query new hot leads from WhatsApp (list_contacts) and prepares high-converting follow-up messages before sending them out.
Runs audits on customer labels (list_contact_labels) or checks which channels are active using list_channels to ensure data consistency across the board.
What Changes When You Connect
- Stop losing leads by context switching. With
list_conversations, your agent pulls every active chat thread—whether it's on WhatsApp or Telegram—into a single list for immediate review. - Save time drafting replies. Instead of opening a client and copying text, use the
send_messagetool to have your AI agent formulate and dispatch replies directly from the terminal. - Deep customer context is instant. Running
get_contact_detailsgives you more than just a name; it pulls associated CRM data and status labels instantly for informed responses. - Know exactly who you're talking to. Use
list_contact_labelsto filter contacts by their current status (e.g., 'Trial User,' 'VIP') before drafting any communication. - See what’s running in the background. Calling
list_automation_flowslets you audit your setup, checking which chatbot trees are active and how they respond to leads.
Real-World Use Cases
Handling a high volume of support tickets
A Support Specialist gets paged at 9 AM. They ask their agent: 'Show me all unread chats from the last three days.' The agent uses list_conversations, identifies five refund requests across WhatsApp and Instagram, and presents them, allowing the specialist to use send_message for a quick resolution.
Targeting specific sales leads
An SDR needs to follow up with VIP clients. They ask their agent to run two tools: first, list_contact_labels and filter for 'VIP'; second, get_contact_details on those filtered IDs. The agent returns the full history for drafting a targeted proposal.
Auditing system readiness
A CRM Manager wants to know if all channels are connected and if any workflows need updating. They call list_channels and then list_automation_flows. This quick check ensures the entire messaging pipeline is healthy before a major campaign launch.
Reacting to abandoned carts
A marketing ops engineer needs to send a reminder. They use list_contacts to pull all contacts labeled 'Abandoned Cart.' Then, using the contact IDs, they call send_message with a specific promotional message.
The Tradeoffs
Assuming one tool handles everything
Trying to send a reply without first confirming the active chat ID. The agent calls send_message('Hello') and it fails because it doesn't know where to send the message.
→
Always start by calling list_conversations. This gives you the necessary conversation ID (conv-xxxx) that you must include when running the send_message tool.
Not knowing what channels are active
Drafting a message intended for Instagram, but forgetting to check if the connection is live. The agent fails because it tries to use a channel that hasn't been connected or listed.
→
Before sending anything, call list_channels. This confirms which platforms are ready and available for your AI client to write to.
Mixing contact lookup with messaging
Asking the agent to 'Send a message about this person.' The tool fails because it needs two distinct steps: first, get_contact_details to confirm the identity, and second, send_message using the resulting ID.
→
When It Fits, When It Doesn't
Use SleekFlow if your core pain point is context switching between multiple messaging platforms (WhatsApp, Instagram, WeChat) while managing customer conversations. You need a unified API that lets an AI client read histories and send replies across all of them.
Don't use this server if you only communicate via email or through a dedicated internal system like Slack. If your goal is simply to manage contacts within one specific platform (e.g., just Stripe), then the other tool category might be better suited. But if it’s 'omnichannel messaging,' SleekFlow is built for that.
Common Questions About SleekFlow MCP
How do I list all connected messaging channels with SleekFlow? +
Call the list_channels tool. This provides a definitive, up-to-date roster of every communication platform (WhatsApp, Telegram, etc.) that your account is currently authorized to use.
Can I find out what labels are on a contact using SleekFlow? +
Yes, first run list_contact_labels to see all available categories. Then, you can apply or check these against specific contacts.
What is the process for sending a message with send_message? +
You must provide three things: the target conversation ID (from list_conversations), the channel name, and the text body. The system uses these to deliver the message.
Does SleekFlow help me see all conversations across different platforms? +
Yes, running list_conversations aggregates chat logs from multiple channels—WhatsApp, Instagram, etc.—into one unified list for your agent to read.
When I use get_contact_details, what type of deep profile data can my agent retrieve for a person? +
The tool retrieves comprehensive details beyond just the name. You pull full profile metadata, including direct CRM ties and any unique categorization labels assigned to that contact.
If I use list_contacts, how do I ensure I see all my synchronized contacts in SleekFlow? +
The tool pulls a complete manifest of every active contact linked within your account. This lets your agent run audits or gather IDs for batch processing.
What kind of information does list_automation_flows provide about the available chatbot trees? +
It returns a full listing of all configured automation workflows and active chatbot trees. Your AI client uses this to know exactly which automated processes are ready to deploy.
What happens if I try to send too many messages using the send_message tool in quick succession? +
The system enforces rate limits for stability. If you exceed your allowed quota, your agent client will receive a specific error code detailing when you can safely retry sending.
Can my AI automatically reply to an agitated customer on WhatsApp? +
Yes. If you point your AI to an active conversation ID, the agent can analyze the raw message history to gauge the emotion. It will draft a polite, perfectly-toned de-escalation message, and if you approve it, it'll trigger the send_message tool pointing directly to the customer's WhatsApp payload.
Can I bulk analyze all incoming conversations over the weekend? +
Absolutely. You can request your agent to invoke the list_conversations command. Your agent can read the active, unassigned threads, categorize them by user intent (e.g., 'refund query', 'feature request'), and provide you a summary dashboard right inside your IDE or markdown interface.
How does the AI know if a customer has an automation flow attached? +
Your agent can call list_automation_flows as well as query the specific get_contact_details tool. This cross-references whether the phone number currently triggers out of an existing flow ID, preventing your AI from interrupting an active bot onboarding session accidentally.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.