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How to Use the Kong Gateway MCP in Pydantic AI

Strictly validated Kong Gateway management for Pydantic AI. Ensure every configuration change meets your schema requirements.

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Connect Kong Gateway MCP to Pydantic AI

Create your Vinkius account to connect Kong Gateway to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Type-safe Kong Gateway operations

Every tool call like `create_plugin` or `update_service` is validated against your Pydantic models at runtime. If the agent proposes an invalid schema, the system stops it immediately. This prevents silent corruption of your gateway state. You get the benefits of agentic speed with the safety of static typing.

Deterministic gateway mutations

Use `create_consumer` and `delete_consumer` with guaranteed structure. The agent receives a clear validation error if it misses a required field. You no longer worry about hallucinated configuration parameters. The framework forces the agent to adhere to your defined gateway structure.

Reliable state introspection

The agent uses `get_route` and `get_upstream` to verify current settings before proposing changes. It treats the gateway as a source of truth. This workflow ensures the agent never operates on stale data. It's built for engineers who prioritize system correctness above all else.

Setup guide

Set up Kong Gateway MCP in Pydantic AI

Prerequisites

  • Python 3.10+ installed
  • pydantic-ai-slim[fastmcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install Pydantic AI with FastMCP

    Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.

  2. 2

    Configure the FastMCPToolset

    Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.

  3. 3

    Create and run your agent

    Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py
from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "kong-gateway-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Kong Gateway tools.",
)

result = await agent.run("List recent Kong Gateway transactions")
print(result.output)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kong Gateway. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Kong Gateway MCP in Pydantic AI

It does. The framework validates every input and output against Pydantic models. You get runtime protection against malformed gateway configurations.
Initialize the `MCPToolset` with your endpoint URL. The agent then registers the tools and starts validating all interactions automatically.
The agent throws a validation error. This forces the system to halt rather than proceeding with corrupted configuration data.
Yes, it supports SSE transports. This allows for real-time interaction between your agent and the gateway infrastructure.
Access is scoped to your endpoint token. The server handles sensitive fields like credentials or certificates, and the Pydantic models ensure these are handled correctly.

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