ChatGen MCP Server for Pydantic AIGive Pydantic AI instant access to 9 tools to Create Bot, Delete Bot, Get Bot, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect ChatGen 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 ChatGen app connector for Pydantic AI is a standout in the Customer Support category — giving your AI agent 9 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 ChatGen "
"(9 tools)."
),
)
result = await agent.run(
"What tools are available in ChatGen?"
)
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 ChatGen MCP Server
Connect your ChatGen account to any AI agent and simplify your conversational marketing and lead management through natural conversation.
Pydantic AI validates every ChatGen tool response against typed schemas, catching data inconsistencies at build time. Connect 9 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 your chatbots, retrieve detailed configuration metadata, and create or update bots programmatically
- Lead Generation — Query and analyze leads captured by your bots to sync with your sales workflows
- Conversation Tracking — Monitor recent chat sessions to understand user interactions and bot performance
- Team Insights — List organizational teams to understand your account structure
The ChatGen MCP Server exposes 9 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 9 ChatGen tools available for Pydantic AI
When Pydantic AI connects to ChatGen through Vinkius, your AI agent gets direct access to every tool listed below — spanning conversational-marketing, lead-capture, chatbot, 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.
Create a new chatbot
Delete a bot
Get details for a specific bot
Get details for a specific lead
List all ChatGen bots
List recent bot conversations
List captured leads
List organizational teams
Update an existing bot
Connect ChatGen to Pydantic AI via MCP
Follow these steps to wire ChatGen 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 ChatGen MCP Server
Pydantic AI provides unique advantages when paired with ChatGen 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 ChatGen integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your ChatGen connection logic from agent behavior for testable, maintainable code
ChatGen + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the ChatGen MCP Server delivers measurable value.
Type-safe data pipelines: query ChatGen with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple ChatGen tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query ChatGen and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock ChatGen responses and write comprehensive agent tests
Example Prompts for ChatGen in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with ChatGen immediately.
"List all my ChatGen bots."
"Show me details for the lead 'lead_999'."
"Find recent bot conversations."
Troubleshooting ChatGen MCP Server with Pydantic AI
Common issues when connecting ChatGen to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiChatGen + Pydantic AI FAQ
Common questions about integrating ChatGen 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.