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Keywords AI MCP Server for Pydantic AIGive Pydantic AI instant access to 11 tools to Check Keywordsai Status, Get Analytics, Get Credits, and more

Built by Vinkius GDPR 11 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Keywords AI 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 Keywords AI app connector for Pydantic AI is a standout in the Developer Tools category — giving your AI agent 11 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 Keywords AI "
            "(11 tools)."
        ),
    )

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

asyncio.run(main())
Keywords AI
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Keywords AI MCP Server

Connect your Keywords AI account to any AI agent and monitor LLM performance.

Pydantic AI validates every Keywords AI tool response against typed schemas, catching data inconsistencies at build time. Connect 11 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

  • Request Logs — List and filter all LLM API calls by model
  • Cost Tracking — Monitor credit balance and usage statistics
  • Analytics — View cost trends, latency metrics, and error rates
  • Model Catalog — Browse available LLM models
  • Team Management — List users and view activity
  • Alerts — Review monitoring thresholds

The Keywords AI MCP Server exposes 11 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 11 Keywords AI tools available for Pydantic AI

When Pydantic AI connects to Keywords AI through Vinkius, your AI agent gets direct access to every tool listed below — spanning llm-observability, api-gateway, cost-tracking, 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.

check_keywordsai_status

Verify API connectivity

get_analytics

Get analytics dashboard

get_credits

Get credit balance

get_request

Get request details

get_usage_stats

Get usage statistics

get_user

Get user details

list_alerts

List monitoring alerts

list_models

List available models

list_requests

List API request logs

list_requests_by_model

List requests by model

list_users

List team users

Connect Keywords AI to Pydantic AI via MCP

Follow these steps to wire Keywords AI into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 11 tools from Keywords AI with type-safe schemas

Why Use Pydantic AI with the Keywords AI MCP Server

Pydantic AI provides unique advantages when paired with Keywords AI through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Keywords AI integration code

03

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

04

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

Keywords AI + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Keywords AI in Pydantic AI

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

01

"Show my current credit balance."

02

"List all requests using GPT-4."

03

"Show analytics dashboard."

Troubleshooting Keywords AI MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Keywords AI + Pydantic AI FAQ

Common questions about integrating Keywords AI MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Keywords AI MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.