How to Use the Typebot MCP in Pydantic AI

Q: How do I list all Typebot workspaces using Pydantic AI?

You use the listworkspaces tool. It gives your agent visibility into every workspace where typebots are deployed.

Q: Can Pydantic AI programmatically start a new Typebot conversation?

Yes, you call startchatsession. This lets the agent run tests or automate interactions with the bot flow directly.

Q: What if I need to delete an old Typebot instance using Pydantic AI?

You use the dedicated deletetypebot tool. Remember, this action permanently removes the specified typebot.

Q: Is it possible to list all deployed conversational Typebots with Pydantic AI?

Yes. The listtypebots function retrieves every bot and lets you filter that list by a specific workspace ID.

Typebot: Type-safe deployment of bot logic with Pydantic AI.

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Connect Typebot MCP to Pydantic AI

Create your Vinkius account to connect Typebot to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Typebot with Pydantic AI

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Monitor and Audit Bots

To understand the full scope, you can call `list_typebots` to list all conversational typebots. This function also lets your agent narrow down results using a workspace ID.

Get Bot Operational Status

Need to check what's running? Use `get_typebot_details` to review the bot’s logic and structure. You can complement this by calling `list_folders` to group related typebots.

Manage Bot Data Collection

When you need data for validation, `list_typebot_results` pulls all collected user responses. This allows your agent to analyze leads or export structured information from a bot flow.

Setup guide

Set up Typebot MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "typebot-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Typebot tools.",
)

result = await agent.run("List recent Typebot transactions")
print(result.output)

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Common questions about Typebot MCP in Pydantic AI

You use the `list_workspaces` tool. It gives your agent visibility into every workspace where typebots are deployed.

Yes, you call `start_chat_session`. This lets the agent run tests or automate interactions with the bot flow directly.

You use the dedicated `delete_typebot` tool. Remember, this action permanently removes the specified typebot.

Yes. The `list_typebots` function retrieves every bot and lets you filter that list by a specific workspace ID.

This MCP Server handles user responses and conversational flow metadata. Specifically, `list_typebot_results` accesses collected user input for analysis.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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