Typebot MCP Server for Pydantic AIGive Pydantic AI instant access to 8 tools to Delete Typebot, Get Typebot Details, List Folders, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Typebot through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Typebot app connector for Pydantic AI 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
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Typebot "
"(8 tools)."
),
)
result = await agent.run(
"What tools are available in Typebot?"
)
print(result.data)
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 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.
Pydantic AI validates every Typebot tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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 Pydantic AI 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 Pydantic AI
When Pydantic AI 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.
Permanently delete a typebot
Essential for reviewing the bot logic. Get details and structure for a specific typebot
Folders are used to group related typebots. List all folders in a workspace
Essential for data analysis and lead export. List collected user responses for a bot
Can be filtered by a specific workspace ID. List all conversational typebots
Workspaces contain folders and bots. List all accessible Typebot workspaces
Requires the unique bot ID. Publish and deploy the latest bot changes
Useful for testing bot flows or automated interactions. Programmatically start a new bot conversation
Connect Typebot to Pydantic AI via MCP
Follow these steps to wire Typebot into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Typebot MCP Server
Pydantic AI provides unique advantages when paired with Typebot through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Typebot integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Typebot connection logic from agent behavior for testable, maintainable code
Typebot + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Typebot MCP Server delivers measurable value.
Type-safe data pipelines: query Typebot with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Typebot tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Typebot and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Typebot responses and write comprehensive agent tests
Example Prompts for Typebot in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Typebot immediately.
"List all typebots in my current workspace."
"Show me the collected results for the 'Lead Gen Flow' bot."
"Publish the latest changes for bot 'bot_10293'."
Troubleshooting Typebot MCP Server with Pydantic AI
Common issues when connecting Typebot to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiTypebot + Pydantic AI FAQ
Common questions about integrating Typebot MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.