Landbot
Landbot is a no-code chatbot builder that enables businesses to create conversational experiences for customer engagement, lead generation, and support across various messaging channels.
Verdict
Common use cases
- Audit which customers opted into WhatsApp campaigns
- Check agent availability before routing support tickets
- Delete test bots after QA cycles
- Verify template parameters before launching broadcasts
- Pull customer phone records for CRM sync
Integration
- Vendor
- Landbot
- Category
- communication
- Auth
- API_KEY
- Tools
- 7
- Composio slug
landbot
Tools
- Delete Botdestructive
Tool to delete a specific bot from your account. use when you need to remove an unused or test bot after confirming the bot id.
- Get Customer By Phone
Tool to retrieve customer details by phone number. use when you need to fetch a customer's profile by their phone. example: "find customer with phone +1234567890".
- List Agents
Tool to retrieve a list of agents in your landbot account. use after authenticating your account to enumerate all agents and their details.
- List Bots
Tool to list all bots in your landbot account. use after authenticating to discover your configured bots.
- List Channels
Tool to list all channels integrated with your account. use after authenticating your account to enumerate available messaging channels and metadata.
- List Customers
Tool to list customers who have interacted with your bot. use when you need to retrieve customer records with optional filters (channel id, opt in, search) and pagination.
- List WhatsApp Templates
Tool to list all whatsapp message templates available for the account. use after obtaining your whatsapp channel id to fetch template ids and parameter counts.
Setup
Setup guide
- 11. In Switchy, open your workspace settings and navigate to the Integrations tab. 2. Search for Landbot and click Connect. 3. You'll be prompted to paste your Landbot API key—generate one by logging into Landbot, going to Settings > API & Webhooks, and creating a new key with full account access. 4. Copy the key and paste it into Switchy, then click Authorize. 5. Switchy confirms the connection by fetching your bot list in the background. 6. Open any Space, type @Landbot followed by a request like 'list all bots', and the MCP will return your configured bots with IDs and metadata. 7. Test further by asking '@Landbot show customers from the last week' to verify customer record access works.
What teammates see: by default, memories from Landbot are scoped to the Space (PROJECT visibility) - you can mark any memory PRIVATE or share it ORG-wide.
Works well with
Top models
Compatibility data appears once enough Spaces have used this MCP together with a given model.
How Switchy teams use it
Starter prompts
List Active Bots
@Landbot list all bots in my account and show their names, IDs, and which channels they're connected to.Open in a Space →
Find Customer by Phone
@Landbot find the customer with phone number +14155552671 and show their interaction history and opt-in status.Open in a Space →
Check WhatsApp Templates
@Landbot list all WhatsApp templates for my account and include the template IDs and how many parameters each requires.Open in a Space →
Enumerate Agents
@Landbot list all agents in my account with their names, IDs, and online status.Open in a Space →
Recent Customer Activity
@Landbot list customers who interacted with any bot in the last seven days, and filter to only those who opted in to marketing messages.Open in a Space →
Example outputs
Illustrative - representative of the model's voice and quality, not literal recordings.
@landbot list all customers who opted in through WhatsApp in the last 30 days
Based on your Landbot account, here are 47 customers who opted in via WhatsApp recently: Maria Santos (+52-555-0123, opted in Jan 15), Carlos Ruiz (+34-600-456789, opted in Jan 18), and 45 others. Each record includes phone number, opt-in timestamp, and channel ID. The most recent opt-in was 2 hours ago. This illustrative example shows how the MCP retrieves filtered customer lists with pagination support for accounts with high interaction volume.
This example uses the List Customers tool with channel and opt-in filters. Requires API key with read access to customer data. Results depend on your bot's actual interaction history. For accounts with thousands of customers, you'll need to handle pagination tokens to retrieve complete datasets beyond the first page.
@landbot find the customer profile for phone number +1-415-555-0199 and show their conversation history
Customer profile retrieved: Jessica Chen, first contacted your bot on December 3rd via the 'Product Support' channel. Phone: +1-415-555-0199, opted in for notifications. The MCP returns basic profile fields (name, phone, opt-in status, channel) but does not include full conversation transcripts—you'd need to cross-reference the customer ID with your Landbot dashboard for message-level details. This illustrative response shows the lookup capability's scope.
This example demonstrates the Get Customer By Phone tool for support or sales follow-up scenarios. The tool returns profile metadata but not conversation content. If you need message history, you'll need to access Landbot's dashboard directly—the MCP focuses on customer identity and channel data, not chat logs.
@landbot check which WhatsApp templates are approved for our account and draft a re-engagement message using the highest-performing template
Your account has 12 approved WhatsApp templates. The 'order_update_v2' template (3 parameters: customer name, order number, delivery date) has the highest usage. Here's a draft re-engagement message: 'Hi {{customer_name}}, your order {{order_number}} is arriving on {{delivery_date}}. Reply to track or modify delivery.' This illustrative example shows how the AI can reason over template metadata to suggest messaging strategies, though actual send operations require separate Landbot workflows.
This example combines the List WhatsApp Templates tool with AI reasoning to recommend messaging tactics. The MCP retrieves template IDs and parameter counts but doesn't send messages directly—you'll configure sends in Landbot's UI. Useful for auditing approved templates before campaign planning. Requires WhatsApp Business API integration already configured in your Landbot account.
Use-case deep-dives
When Landbot MCP makes sense for bot cleanup
A 6-person support team runs four Landbot chatbots across web and WhatsApp. Every quarter, they audit which bots still get traffic and which templates are stale. The Landbot MCP works here because the team needs read-only visibility into bot configs, customer lists, and WhatsApp templates without logging into the dashboard. List Bots and List WhatsApp Templates surface the inventory in one prompt. Delete Bot lets them retire test instances after confirming the ID. The trade-off: if your team only checks this once a year, the MCP setup overhead isn't worth it—just use the Landbot UI. If you audit monthly or tie bot metrics into Slack standups, the MCP saves 15 minutes per check.
Landbot MCP for real-time customer context
A 3-person sales team uses Landbot for lead qualification on their site. When a prospect books a call, the rep needs the full conversation history and opt-in status before dialing. The Landbot MCP's Get Customer By Phone and List Customers tools pull that context into Switchy without switching tabs. The rep pastes the phone number, gets the profile, and sees which bot flow the lead completed. This works when your team handles under 50 calls a week—above that volume, you need a CRM sync, not an MCP query. The MCP shines for small teams who want customer context on-demand without building a Zapier chain or paying for HubSpot.
Using Landbot MCP to document client handoffs
A 2-person agency builds Landbot flows for e-commerce clients. At project close, they document which bots are live, which agents have access, and which channels are connected. The Landbot MCP's List Bots, List Agents, and List Channels tools generate that snapshot in one Switchy prompt instead of screenshotting the dashboard. The output goes straight into the handoff doc. This saves 20 minutes per client if you're handing off 4+ projects a quarter. The limitation: the MCP doesn't export bot logic or flow diagrams, so you still need Landbot's native export for that. Use the MCP for account-level inventory, not flow documentation.
Frequently asked
What does the Landbot MCP let me do in Switchy?
The Landbot MCP connects your Landbot account to Switchy so AI can read bot configurations, customer lists, agent rosters, and WhatsApp templates. It can also delete test bots and look up customer profiles by phone number. Think of it as giving AI read access to your Landbot workspace, plus light cleanup tasks.
Do I need admin access to connect Landbot?
You need an API key from your Landbot account settings. Landbot doesn't publish granular permission tiers for API keys, so assume whoever generates the key has full account access. If your team restricts API key creation to admins, you'll need admin help to set this up.
Can the Landbot MCP send messages or trigger bot flows?
No. The MCP reads data—bots, customers, channels, templates—and can delete bots, but it can't send messages, start conversations, or modify flows. If you need to trigger outbound WhatsApp messages or update bot logic, use Landbot's webhooks or their full API directly.
Why use this instead of logging into Landbot?
Use the MCP when you want AI to answer questions like "how many customers opted in this month" or "which bots are live" without opening Landbot's dashboard. It's faster for audits, reporting, and cross-referencing customer data with other tools in Switchy. For building or editing bots, stick with Landbot's UI.
Who on my team should connect the Landbot MCP?
Whoever owns your Landbot API keys—usually a marketing ops lead or customer success manager. Since the key grants full account access, don't share it with junior team members unless your Landbot plan supports scoped keys. One connection covers the whole Switchy workspace.