Can I search for a specific lead or contact by name?

Yes! Use the `list_contacts` tool and provide the `search_text` parameter with the name, email, or details you are looking for. The agent will return the matching profiles.

How do I review the chat history of a conversation?

First, use `list_chats` to find the active or historical session. Then, use `get_chat_history` with the Chat ID to retrieve the full log of messages.

Can I send an OTP SMS to a user?

Yes. Use the `send_otp` action and provide the user's phone number (with the country code). BotPenguin will handle the integration to send the verification code.

BotPenguin MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: BotPenguin
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 BotPenguin 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 BotPenguin "
            "(8 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

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DLPData protection

V8 IsolateSandboxed

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<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 BotPenguin MCP Server

Connect your BotPenguin account to any AI agent and orchestrate your customer conversations, lead generation, and support workflows through natural language.

Pydantic AI validates every BotPenguin 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

Contact Management — List and search for contacts or leads collected by your chatbots across multiple channels.
Chat Oversight — Retrieve active and historical chat sessions to monitor agent and bot performance.
Conversation Logging — Access the full message history for specific chat sessions.
Message Automation — Send messages directly into active chats to assist users programmatically.
Authentication Support — Trigger OTP SMS messages to verify user phone numbers.
Team Coordination — List all configured tags and human agents to ensure proper lead routing.

The BotPenguin 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 BotPenguin to Pydantic AI via MCP

Follow these steps to integrate the BotPenguin 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 BotPenguin with type-safe schemas

Why Use Pydantic AI with the BotPenguin MCP Server

Pydantic AI provides unique advantages when paired with BotPenguin 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 BotPenguin integration code

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

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

BotPenguin + Pydantic AI Use Cases

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

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

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

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

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

BotPenguin MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect BotPenguin to Pydantic AI via MCP:

get_chat_history

Retrieve message history of a chat

get_contact

Get details of a specific contact

list_agents

List all human agents/operators

list_chats

List active chat sessions

list_contacts

Optional search text. List all BotPenguin contacts/leads

list_tags

List all contact tags

send_message

Send a message in a specific chat

send_otp

Send an OTP SMS to verify a phone number

Example Prompts for BotPenguin in Pydantic AI

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

"List the most recent contacts in BotPenguin."

"Show the chat history for chat session chat_123."

"Send an OTP SMS to +1555998877."

Troubleshooting BotPenguin MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

BotPenguin + Pydantic AI FAQ

Common questions about integrating BotPenguin 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 BotPenguin MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.