Landbot MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 12 tools to Get Account Info, Get Customer Details, Handoff To Agent, and more
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Landbot through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
Ask AI about this App Connector for OpenAI Agents SDK
The Landbot app connector for OpenAI Agents SDK is a standout in the Customer Support category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Landbot Assistant",
instructions=(
"You help users interact with Landbot. "
"You have access to 12 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Landbot"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Landbot MCP Server
Connect your Landbot account to any AI agent and manage chatbots through natural conversation.
The OpenAI Agents SDK auto-discovers all 12 tools from Landbot through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Landbot, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- Bot Management — List bots, inspect configurations, and track performance
- Conversation Tracking — Browse conversations, read messages, and send replies
- Customer Database — List customers with engagement data and conversation history
- Flow Monitoring — Track chatbot flows and their conversion metrics
- Channel Management — Monitor WhatsApp, Web, and API channels
- Analytics — Access conversation metrics, response rates, and bot performance
The Landbot MCP Server exposes 12 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 Landbot tools available for OpenAI Agents SDK
When OpenAI Agents SDK connects to Landbot through Vinkius, your AI agent gets direct access to every tool listed below — spanning chatbot, conversational-marketing, lead-capture, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Check API status
Get user profile
Assign to human
List available bots
List chatbot users
Get event configs
List support agents
Send chat image
Send chat message
Send WA template
Start bot flow
Set user property
Connect Landbot to OpenAI Agents SDK via MCP
Follow these steps to wire Landbot into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install the SDK
pip install openai-agents in your Python environmentReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comRun the script
python agent.pyExplore tools
Why Use OpenAI Agents SDK with the Landbot MCP Server
OpenAI Agents SDK provides unique advantages when paired with Landbot through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Landbot + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Landbot MCP Server delivers measurable value.
Automated workflows: build agents that query Landbot, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Landbot, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Landbot tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Landbot to resolve tickets, look up records, and update statuses without human intervention
Example Prompts for Landbot in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Landbot immediately.
"Show all bots with conversation counts and the latest customer conversations."
"Show the conversation flow and analytics for the Lead Qualifier bot."
"List all customers and send a reply to Ana's conversation."
Troubleshooting Landbot MCP Server with OpenAI Agents SDK
Common issues when connecting Landbot to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Landbot + OpenAI Agents SDK FAQ
Common questions about integrating Landbot MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.