Landbot MCP Server for OpenAI Agents SDK 8 tools — connect in under 2 minutes
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 MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 8 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
Engage your conversational pipelines through Landbot instantly using your AI assistant. Route leads, send custom programmatic messages to open channels, or check active interactions without checking external software tools.
The OpenAI Agents SDK auto-discovers all 8 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: Oversee and pull active bot matrices.
- Customer Operations: Send automated text messages securely to connected accounts.
- Lead Routing: Reassign critical pipeline threads directly to live agents programmatically.
The Landbot MCP Server exposes 8 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.
How to Connect Landbot to OpenAI Agents SDK via MCP
Follow these steps to integrate the Landbot MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 8 tools from Landbot
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
Landbot MCP Tools for OpenAI Agents SDK (8)
These 8 tools become available when you connect Landbot to OpenAI Agents SDK via MCP:
assign_agent
Route conversation from bot to live agent status
get_bot
Get a single bot details by ID
get_customer
Retrieve specific metadata of one customer
get_messages
Fetch the chat sequence messages for a given customer context
list_bots
List all accessible bots in Landbot
list_customers
List recent customers interacting with bots
search_customers
Search for a particular customer by email
send_text_message
Send a message programmatically to a customer conversation
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.
"List standard bots running active pipelines right now."
"Fetch the entire transcription log for customer ID 98453."
"Force assign the highest severity angry customer ticket to Agent Sarah."
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.Does the SDK support streaming responses?
Connect Landbot with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Landbot to OpenAI Agents SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.