Kong (AI API Gateway) MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Kong (AI API Gateway) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Kong (AI API Gateway) "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Kong (AI API Gateway)?"
)
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 Kong (AI API Gateway) MCP Server
Connect your Kong API Gateway instance to any AI agent and take full control of your API lifecycle and AI traffic management through natural conversation.
Pydantic AI validates every Kong (AI API Gateway) tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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
- Service Orchestration — List backend services and create new upstream definitions defining URLs and protocols directly from your agent
- Route Management — Configure inbound routing rules to map client requests to backend services based on specific paths or hostnames
- AI Plugin Control — Apply and configure the
ai-proxyplugin to enable LLM routing, model providers, and key encapsulation securely - Operational Patching — Update existing plugin configurations in real-time, allowing you to adjust rate limits or swap AI models dynamically
- Consumer CRM — Manage consumer profiles and generate API keys for
key-authplugins to track specific user or tenant usage - Infrastructure Audit — Discover enabled plugins across your gateway and remove unused modules instantly to maintain a clean proxy pipeline
The Kong (AI API Gateway) MCP Server exposes 10 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 Kong (AI API Gateway) to Pydantic AI via MCP
Follow these steps to integrate the Kong (AI API Gateway) 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 10 tools from Kong (AI API Gateway) with type-safe schemas
Why Use Pydantic AI with the Kong (AI API Gateway) MCP Server
Pydantic AI provides unique advantages when paired with Kong (AI API Gateway) 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 Kong (AI API Gateway) integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Kong (AI API Gateway) connection logic from agent behavior for testable, maintainable code
Kong (AI API Gateway) + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Kong (AI API Gateway) MCP Server delivers measurable value.
Type-safe data pipelines: query Kong (AI API Gateway) with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Kong (AI API Gateway) tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Kong (AI API Gateway) and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Kong (AI API Gateway) responses and write comprehensive agent tests
Kong (AI API Gateway) MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Kong (AI API Gateway) to Pydantic AI via MCP:
create_ai_plugin
Frequently used for enabling the `ai-proxy` plugin for LLM routing and key encapsulation. Apply a new Plugin (like AI Proxy) to a specific Service
create_consumer_key
Generate an API Key credential for a Kong Consumer
create_route
Create a new Route to expose a Service in Kong
create_service
The payload must define the upstream URL, name, and protocol information. Create a new backend Service in Kong
delete_plugin
Delete and permanently remove a Plugin from the Kong Gateway
list_consumers
List all Consumer profiles registered in Kong
list_plugins
g., Rate Limiting, AI Proxy, Key Auth) currently configured globally or scoped to specific Services/Routes. List all enabled Plugins on the Kong Gateway
list_routes
List all routing rules configured in the Kong API Gateway
list_services
List all Services registered in the Kong API Gateway
update_plugin
Useful for adjusting rate limits dynamically or swapping AI model providers under heavy load. Update the configuration of an existing Kong Plugin
Example Prompts for Kong (AI API Gateway) in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Kong (AI API Gateway) immediately.
"List all registered services in my Kong Gateway"
"Add the 'ai-proxy' plugin to service ID '123-abc' using OpenAI"
"Who are the registered consumers in our gateway?"
Troubleshooting Kong (AI API Gateway) MCP Server with Pydantic AI
Common issues when connecting Kong (AI API Gateway) to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiKong (AI API Gateway) + Pydantic AI FAQ
Common questions about integrating Kong (AI API Gateway) 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.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Kong (AI API Gateway) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Kong (AI API Gateway) to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.