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Typebot MCP Server for LangChainGive LangChain instant access to 8 tools to Delete Typebot, Get Typebot Details, List Folders, and more

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Typebot through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this App Connector for LangChain

The Typebot app connector for LangChain is a standout in the Productivity category — giving your AI agent 8 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "typebot": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Typebot, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Typebot
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Typebot MCP Server

Connect your Typebot account to any AI agent and simplify how you build, manage, and analyze your conversational assistants through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Typebot through native MCP adapters. Connect 8 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

  • Bot Management — List all typebots across your workspaces and folders, and retrieve detailed metadata and flow structures.
  • Deployment Control — Publish the latest bot changes to production instantly without leaving your agent.
  • Result Analysis — List and export user submissions and conversation results to track leads and performance.
  • Organization Oversight — Manage workspaces and folders to keep your conversational projects structured.
  • Session Testing — Programmatically start new chat sessions to verify bot logic and user experiences.

The Typebot MCP Server exposes 8 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 8 Typebot tools available for LangChain

When LangChain connects to Typebot through Vinkius, your AI agent gets direct access to every tool listed below — spanning chatbot-builder, conversational-forms, automation, 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.

delete_typebot

Permanently delete a typebot

get_typebot_details

Essential for reviewing the bot logic. Get details and structure for a specific typebot

list_folders

Folders are used to group related typebots. List all folders in a workspace

list_typebot_results

Essential for data analysis and lead export. List collected user responses for a bot

list_typebots

Can be filtered by a specific workspace ID. List all conversational typebots

list_workspaces

Workspaces contain folders and bots. List all accessible Typebot workspaces

publish_typebot

Requires the unique bot ID. Publish and deploy the latest bot changes

start_chat_session

Useful for testing bot flows or automated interactions. Programmatically start a new bot conversation

Connect Typebot to LangChain via MCP

Follow these steps to wire Typebot into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 8 tools from Typebot via MCP

Why Use LangChain with the Typebot MCP Server

LangChain provides unique advantages when paired with Typebot through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine Typebot MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Typebot queries for multi-turn workflows

Typebot + LangChain Use Cases

Practical scenarios where LangChain combined with the Typebot MCP Server delivers measurable value.

01

RAG with live data: combine Typebot tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query Typebot, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain Typebot tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every Typebot tool call, measure latency, and optimize your agent's performance

Example Prompts for Typebot in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Typebot immediately.

01

"List all typebots in my current workspace."

02

"Show me the collected results for the 'Lead Gen Flow' bot."

03

"Publish the latest changes for bot 'bot_10293'."

Troubleshooting Typebot MCP Server with LangChain

Common issues when connecting Typebot to LangChain through the Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Typebot + LangChain FAQ

Common questions about integrating Typebot MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.