Can I see who is currently visiting my website?

Yes! Use the `list_website_visitors` tool. The agent will return a list of recent and active visitors, including their names, emails, and location if available.

How do I reply to a specific customer chat?

Use the `send_agent_message` tool with the unique chat ID. Your agent will post the message directly into the Chaport conversation.

Where do I generate my Chaport API Token?

Log in to your Chaport account and go to **Settings → API**. You can generate and copy your API token from that section.

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

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

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

asyncio.run(main())

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* 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 Chaport MCP Server

Connect your Chaport account to any AI agent and take full control of your customer messaging operations through natural conversation. Streamline how you engage with website visitors and manage your support team.

Pydantic AI validates every Chaport 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

Live Messaging — Send and receive messages in active chat sessions natively
Visitor Intelligence — List and retrieve details for recent website visitors and their contact info flawlessly
Conversation History — Access full chat histories and event logs to understand customer context securely
Operator Oversight — Monitor agent availability and list all operators in your account in real-time
Status Management — Identify which agents are currently online to manage support load flawlessly
Agent Insights — Retrieve your own operator profile and account metadata directly within your workspace

The Chaport 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 Chaport to Pydantic AI via MCP

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

Why Use Pydantic AI with the Chaport MCP Server

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

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

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

Chaport + Pydantic AI Use Cases

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

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

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

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

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

Chaport MCP Tools for Pydantic AI (8)

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

get_chat_history

Retrieve the message history and events for a specific chat

get_my_agent_profile

Retrieve information about the authenticated agent

get_visitor_details

Get detailed information for a specific visitor

get_visitor_last_chat

Retrieve the last chat session for a specific visitor

list_chaport_operators

List all operators in your Chaport account

list_online_agents

List all agents who are currently online

list_website_visitors

List recent visitors to your website

send_agent_message

Send a message to a visitor in a specific chat

Example Prompts for Chaport in Pydantic AI

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

"List all website visitors from the last hour."

"Which support agents are currently online in Chaport?"

"Show me the message history for chat ID 123456."

Troubleshooting Chaport MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Chaport + Pydantic AI FAQ

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