OpenCost (K8s Cost) MCP Server for Pydantic AIGive Pydantic AI instant access to 6 tools to Get Allocation, Get Assets, Get Cloud Cost, and more

Name: OpenCost (K8s Cost)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect OpenCost (K8s Cost) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The OpenCost (K8s Cost) MCP Server for Pydantic AI is a standout in the Cloud Infrastructure category — giving your AI agent 6 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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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 OpenCost (K8s Cost) "
            "(6 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in OpenCost (K8s Cost)?"
    )
    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 OpenCost (K8s Cost) MCP Server

Connect your OpenCost instance to any AI agent to gain real-time visibility into your Kubernetes spending and infrastructure efficiency through natural language.

Pydantic AI validates every OpenCost (K8s Cost) tool response against typed schemas, catching data inconsistencies at build time. Connect 6 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

Workload Allocation — Query costs and resources allocated to clusters, nodes, namespaces, controllers, and pods using get_allocation.
Asset Inspection — Retrieve backing cost data for physical infrastructure like Nodes, Disks, and Load Balancers via get_assets.
Cloud Billing Integration — Access AWS CUR, Azure Export, and GCP Billing data directly with get_cloud_cost to reconcile K8s costs with provider bills.
Third-Party Costs — Track external service expenses (e.g., Datadog, MongoDB Atlas) using custom cost timeseries and total summary tools.
Granular Filtering — Aggregate data by labels, annotations, or service levels to understand exactly where your budget is going.

The OpenCost (K8s Cost) MCP Server exposes 6 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 OpenCost (K8s Cost) tools available for Pydantic AI

When Pydantic AI connects to OpenCost (K8s Cost) through Vinkius, your AI agent gets direct access to every tool listed below — spanning kubernetes, cost-optimization, cloud-billing, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get allocation on OpenCost (K8s Cost)

Query costs and resources allocated to Kubernetes workloads

get

Get assets on OpenCost (K8s Cost)

Retrieve backing cost data broken down by individual assets

get

Get cloud cost on OpenCost (K8s Cost)

Retrieve cloud cost data directly from cloud provider billing reports

get

Get custom cost timeseries on OpenCost (K8s Cost)

g., Datadog, MongoDB Atlas). Get samples of third-party service costs over time steps

get

Get custom cost total on OpenCost (K8s Cost)

Get summary of third-party costs over a window

set

Set log level on OpenCost (K8s Cost)

Change OpenCost log level at runtime

Connect OpenCost (K8s Cost) to Pydantic AI via MCP

Follow these steps to wire OpenCost (K8s Cost) into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 6 tools from OpenCost (K8s Cost) with type-safe schemas

Why Use Pydantic AI with the OpenCost (K8s Cost) MCP Server

Pydantic AI provides unique advantages when paired with OpenCost (K8s Cost) 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 OpenCost (K8s Cost) integration code

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

Dependency injection system cleanly separates your OpenCost (K8s Cost) connection logic from agent behavior for testable, maintainable code

OpenCost (K8s Cost) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the OpenCost (K8s Cost) MCP Server delivers measurable value.

Type-safe data pipelines: query OpenCost (K8s Cost) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple OpenCost (K8s Cost) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query OpenCost (K8s Cost) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock OpenCost (K8s Cost) responses and write comprehensive agent tests

Example Prompts for OpenCost (K8s Cost) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with OpenCost (K8s Cost) immediately.

"Show me the cost allocation for all namespaces over the last 7 days."

"What are the backing asset costs for our nodes today?"

"Get the total summary for third-party service costs for the current month."

Troubleshooting OpenCost (K8s Cost) MCP Server with Pydantic AI

Common issues when connecting OpenCost (K8s Cost) to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

OpenCost (K8s Cost) + Pydantic AI FAQ

Common questions about integrating OpenCost (K8s Cost) 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 OpenCost (K8s Cost) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.