Can I see which phrases my bot failed to understand?

Yes! Use the `list_training_data` tool. The agent will return a list of unrecognized phrases, helping you identify what needs to be added to your bot's training set.

How do I list all the interactions in a specific story?

Use the `list_story_interactions` tool with the unique story ID. Your agent will fetch all interaction blocks and their configurations.

Where do I find my ChatBot Access Token?

Log in to your ChatBot account and go to the settings section. Look for 'API' or 'Integrations' to generate and copy your Developer Access Token.

ChatBot.com MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: ChatBot.com
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect ChatBot.com through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 ChatBot.com "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in ChatBot.com?"
    )
    print(result.data)

asyncio.run(main())

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 ChatBot.com MCP Server

Connect your ChatBot.com account to any AI agent and take full control of your conversational automation through natural conversation. Streamline how you build and monitor your customer service bots.

Pydantic AI validates every ChatBot.com 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

Story Oversight — List and retrieve details for all conversational stories and bot workflows natively
Interaction Intelligence — Access and monitor interactions within specific stories to understand user paths flawlessly
User Management — List all users who have interacted with your bot and retrieve their detailed profiles securely
Integration Auditing — List and review configured webhook integrations and entities flawlessly
Training Logistics — Retrieve unrecognized phrases to identify areas where your bot needs additional training flawlessly
System Metadata — Access entity definitions and core account structures directly within your workspace

The ChatBot.com 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.

How to Connect ChatBot.com to Pydantic AI via MCP

Follow these steps to integrate the ChatBot.com MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from ChatBot.com with type-safe schemas

Why Use Pydantic AI with the ChatBot.com MCP Server

Pydantic AI provides unique advantages when paired with ChatBot.com 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 ChatBot.com integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your ChatBot.com connection logic from agent behavior for testable, maintainable code

ChatBot.com + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the ChatBot.com MCP Server delivers measurable value.

Type-safe data pipelines: query ChatBot.com with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple ChatBot.com tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query ChatBot.com and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock ChatBot.com responses and write comprehensive agent tests

ChatBot.com MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect ChatBot.com to Pydantic AI via MCP:

get_chatbot_user_details

Get details for a specific chatbot user

get_story_details

Get detailed information for a specific story

list_chatbot_entities

List custom entities used for NLP matching

list_chatbot_stories

List all stories (bot workflows)

list_chatbot_users

List all users who have interacted with the bot

list_chatbot_webhooks

List all configured webhook integrations

list_story_interactions

List all interactions within a story

list_training_data

List unrecognized phrases that require bot training

Example Prompts for ChatBot.com in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with ChatBot.com immediately.

"List all conversational stories in my account."

"What training data is pending review?"

"Search for users who interacted with the bot today."

Troubleshooting ChatBot.com MCP Server with Pydantic AI

Common issues when connecting ChatBot.com to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

ChatBot.com + Pydantic AI FAQ

Common questions about integrating ChatBot.com MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your ChatBot.com MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.