Texter MCP. Manage chats, messages & labels with natural conversation.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Texter MCP Server handles all your multi-channel communication needs. Use it to manage chats, send template messages via WhatsApp or Instagram, list conversations across multiple channels, and organize leads with custom labels.
It lets your AI client handle customer service tasks—like resolving tickets or retrieving message history—without leaving the chat window.
What your AI agents can do
Add label to texter chat
Assigns a specific label to an existing chat conversation for organization.
Get texter chat details
Fetches comprehensive metadata and history for a single, specified chat.
List texter channels
Lists all the messaging channels (WhatsApp, Instagram, etc.) that are connected to your account.
The agent fetches full metadata, message lists, and conversation history for any specified chat ID.
You send a direct message to an active chat, or you trigger a structured template message for bulk outreach.
The agent marks chats as resolved/closed and applies custom labels to track status and department ownership.
You list all connected channels, departments, or available chat labels for oversight.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Texter MCP Server: 10 Tools for Messaging Ops
These tools give your AI client direct control over every aspect of your messaging workspace—from listing chats to sending template messages and closing tickets.
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 Texter on Vinkius019dd171add label to texter chat
Assigns a specific label to an existing chat conversation for organization.
019dd171get texter chat details
Fetches comprehensive metadata and history for a single, specified chat.
019dd171list texter channels
Lists all the messaging channels (WhatsApp, Instagram, etc.) that are connected to your account.
019dd171list texter chats
Retrieves a list of every currently active chat conversation in your workspace.
019dd171list texter departments
Lists the different departments set up within your Texter account structure.
019dd171list texter labels
Shows all the custom labels you've created for organizing chats.
019dd171list texter messages
Retrieves a list of messages that have been sent within a specific chat thread.
019dd171resolve texter chat
Marks and closes an active chat conversation, signifying the issue is handled.
019dd171send texter message
Sends a standard message to any currently active chat thread.
019dd171send texter template
Triggers an official WhatsApp or Messenger template message for outreach campaigns.
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Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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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 Texter. 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 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Tracking a customer conversation shouldn't involve jumping between five different tabs.
Today, resolving a simple inquiry means opening the chat dashboard, finding the right channel (WhatsApp vs. Insta), scrolling up to confirm details, making notes in a separate CRM tab, and finally, manually clicking 'Resolve' on three different screens just to mark it done.
With the Texter MCP Server, you tell your agent: 'Find the conversation with John Doe, check the history, resolve it, and label it Billing-Fixed.' The server runs `get_texter_chat_details`, executes `resolve_texter_chat`, and applies the label—all in one command. You get organized data instantly.
Texter MCP Server: Send automated messages via templates.
Before, sending a mass update meant drafting individual messages for each platform or manually copying and pasting the same text repeatedly. If you missed one customer, the campaign was incomplete.
Now, your agent uses `send_texter_template`. You define the template once—say, 'Order Confirmed'—and pass in variables like the order ID and date. The server handles sending that structured message across all necessary channels automatically. It’s reliable.
What you can do with this MCP connector
Texter MCP Server handles your whole communication stack, connecting your AI client directly to chats across WhatsApp and Instagram. You don't have to leave the window to manage customer service tasks or send out campaign messages; your agent does it all.
Retrieving Chat History and Details: When you need context on an issue, your agent fetches full metadata for a specific chat ID using get_texter_chat_details. If you just want to see what was said in a thread without the deep dive, list_texter_messages gives you a list of messages sent within that particular chat.
To get a birds-eye view of everything happening right now, you can call list_texter_chats, which retrieves every active conversation in your workspace. You'll also be able to check out all the connected messaging channels—whether it's WhatsApp or Instagram—by running list_texter_channels.
Initiating Messages and Campaigns: Need to talk to a customer? Your agent sends a standard message directly into an active chat thread using send_texter_message. For bigger outreach, you can trigger official template messages for campaigns via send_texter_template, which works specifically through WhatsApp or Messenger. If you need to reach out but don't know which department owns the conversation, you can first check out list_texter_departments to see all the different operational departments set up in your Texter account structure.
Organizing and Closing Conversations: When a customer issue is solved, you mark it as such. Your agent runs resolve_texter_chat to close an active chat conversation, signaling that the ticket's handled. To keep your data clean and traceable, you can apply custom labels using add_label_to_texter_chat, assigning a specific label to any existing chat conversation for organization.
You also get full visibility into how organized your chats are by calling list_texter_labels to see every single custom label you've created.
This setup lets your AI client manage everything from viewing the initial list of conversations via list_texter_chats, getting the deep message history using list_texter_messages, and finally marking the whole thing as done with resolve_texter_chat. You can also use these same tools to discover the workspace structure, confirming all available channels with list_texter_channels or checking out department ownership via list_texter_departments.
Your agent handles the entire lifecycle: listing chats, pulling chat details, sending messages, adding labels for tracking, and resolving the ticket when it's done. It’s everything you need to keep your customer data straight and actionable.
019dd171-771c-73cf-bc3b-a2fb3562cad0 
How Texter MCP Works
- 1 First, subscribe to the Texter server and provide your API token and Project ID in the AI client settings.
- 2 Next, prompt your agent with a specific action—for example: 'List all active chats' or 'Resolve chat ABC and add label Support-Fixed'.
- 3 The agent runs the required tool call (like
list_texter_chatsorresolve_texter_chat) and returns the structured data to you for immediate review.
The bottom line is that it turns your AI client into a direct chat management interface, letting you run complex tasks with simple prompts.
Who Is Texter MCP For?
This server is built for the ops engineer who needs to manage high volumes of customer conversations across multiple platforms without switching tabs. It's critical for support and marketing teams dealing with ticket backlogs or running automated drip campaigns.
Uses the agent to pull up a chat history (get_texter_chat_details), respond quickly (send_texter_message), and then close out the ticket by resolving it and adding labels.
Runs template campaigns to new leads (send_texter_template) or lists departments to segment outreach efforts.
Checks system health by listing all connected channels (list_texter_channels) and monitoring chat volume without logging into the main workspace.
What Changes When You Connect
- Close out tickets fast. Use
resolve_texter_chatandadd_label_to_texter_chatto mark conversations as finished. The agent handles the state change instantly, keeping your team's records clean. - Run targeted campaigns without manual effort.
send_texter_templatelets you deploy localized template messages for new leads directly via AI commands. - See everything at a glance. Running
list_texter_chatsgives you an immediate overview of active threads, whileget_texter_chat_detailsdives deep into the full conversation history when needed. - Stay organized across platforms. You can use
list_texter_departmentsandlist_texter_labelsto understand your entire workspace setup before routing a new ticket. - Handle diverse communication types. Whether it's a live chat reply (
send_texter_message) or an automated drip campaign, the server handles both through dedicated tools.
Real-World Use Cases
The Overdue Inquiry
A lead messages in, but the thread is old and needs context. The agent runs get_texter_chat_details to pull the full message history. You read it, figure out the answer, then use send_texter_message to reply. Finally, you run resolve_texter_chat and add_label_to_texter_chat so the record is closed for billing.
The Mass Announcement
Marketing needs to send a product update to 50 customers. Instead of manually composing messages, the agent uses send_texter_template, selecting the 'announcement' template and passing in dynamic fields like the new version number.
Auditing Channels
The ops manager needs to know if Instagram or WhatsApp is connected before starting a campaign. They run list_texter_channels to verify connectivity, ensuring no channels are missed in the deployment plan.
Triage and Ownership
A new chat comes in that needs to be routed. The agent first runs list_texter_departments, identifies 'Billing' as the correct team, and then applies a specific label using add_label_to_texter_chat before handing it off.
The Tradeoffs
Copy-pasting chat details.
A support agent manually copies message IDs and channel names into a spreadsheet to track ticket progress, wasting time and risking errors.
→
Use list_texter_chats and then get_texter_chat_details. Your AI client pulls all necessary metadata directly from the server, keeping everything in one place.
Guessing which channel is used.
A team member starts a campaign assuming everyone uses WhatsApp, only to find critical leads are on Instagram because they forgot to check the available channels.
→
Always run list_texter_channels first. This shows every connected messaging platform so you target your outreach correctly.
Leaving chats open when done.
A chat thread is solved, but left marked as 'Active' in the system because no one remembered to close it out or label it properly.
→
When a task is finished, run resolve_texter_chat and then use add_label_to_texter_chat. This closes the loop and organizes the data immediately.
When It Fits, When It Doesn't
Use this server if your primary goal is managing conversations across multiple messaging platforms (WhatsApp, Instagram) and you need to automate manual workflow steps like labeling, resolving tickets, or sending templated messages. It's perfect for support teams with high ticket volume.
Don't use it if you just need to read static data from a database (use a generic database tool). Don't use it if you require real-time video streaming or live collaboration rooms—this is purely focused on message transport and chat state. If you only need to send messages without templates, send_texter_message works, but for structured campaigns, rely on send_texter_template.
Common Questions About Texter MCP
How do I list all active chats using list_texter_chats? +
You prompt the agent with 'List all active chats.' The tool runs and returns a comprehensive list of every ongoing conversation ID, letting you know exactly which threads need attention.
What's the difference between send_texter_message and send_texter_template? +
Use send_texter_message for free-form replies to an active chat. Use send_texter_template when you need to trigger a structured, pre-approved message type, like 'Order Confirmation,' ensuring compliance.
Can I organize chats after they are resolved using add_label_to_texter_chat? +
Yes. You must first run resolve_texter_chat to close the ticket, and then you can follow up by calling add_label_to_texter_chat to categorize it (e.g., 'Needs Follow-up').
How do I check which messaging channels are connected? +
Run the list_texter_channels tool. This gives you a clear list of all linked platforms, like WhatsApp and Instagram, confirming your operational scope.
How do I retrieve all messages in a specific chat using list_texter_messages? +
It returns a chronological list of every message sent within that conversation. You must provide the unique chat ID and specify a time range to pull the exact data you need for context.
What happens to a chat when I use resolve_texter_chat? +
The chat status changes from active to resolved, but the message history remains intact. This action is purely organizational and keeps the conversation accessible in your records for auditing.
What fields must I include when sending a template message using send_texter_template? +
You need to supply all dynamic components defined within that specific template. This ensures the messaging is personalized and adheres to platform requirements like WhatsApp's rules.
How does list_texter_departments help with team assignments? +
It lists every department configured in your Texter workspace. Your agent uses this data to understand which teams exist, allowing it to correctly assign or route incoming chats.
Can I see the history of a specific chat via AI? +
Yes! Use the list_texter_messages tool and provide the Chat ID. Your agent will retrieve the complete message log for that conversation.
How do I send a WhatsApp template with parameters? +
Use the send_texter_template action. Provide the destination number, Template ID, language, and a JSON array for the dynamic components to personalize the message.
Is it possible to assign a label to a conversation via AI? +
Absolutely. Use the add_label_to_texter_chat tool. Provide the Chat ID and the Label ID to organize your inbox programmatically.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.