How do I get a DevSkiller API Key?

Log in to your DevSkiller account, navigate to **Settings > API**, and you can generate or retrieve your unique API Key from that section.

Can the agent show the candidate's code?

This integration currently focuses on retrieving scores, statuses, and technical reports. Full source code review should be performed within the DevSkiller platform.

How do I invite a candidate via chat?

You can use the invite_candidate_to_test tool. You will need to provide the candidate's email address and the specific Test ID from your catalog.

DevSkiller MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: DevSkiller
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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 DevSkiller "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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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 DevSkiller MCP Server

Integrate DevSkiller, the technical screening and talent assessment platform, directly into your AI workflow. Manage your candidate pipeline, send test invitations, and retrieve detailed assessment reports and skill scores using natural language.

Pydantic AI validates every DevSkiller 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

Candidate Oversight — List and search for candidates in your database and monitor their current assessment status.
Test Management — Access your library of available technical tests, coding tasks, and quizzes.
Invitation Tracking — Monitor sent test invitations and track candidate progress in real-time.
Performance Analytics — Retrieve full assessment reports with granular skill scores and performance metrics.

The DevSkiller 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 DevSkiller to Pydantic AI via MCP

Follow these steps to integrate the DevSkiller 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 DevSkiller with type-safe schemas

Why Use Pydantic AI with the DevSkiller MCP Server

Pydantic AI provides unique advantages when paired with DevSkiller 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 DevSkiller integration code

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

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

DevSkiller + Pydantic AI Use Cases

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

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

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

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

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

DevSkiller MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect DevSkiller to Pydantic AI via MCP:

get_account_metadata

Retrieve metadata and limits for your DevSkiller account

get_candidate_assessment_report

Retrieve the full assessment report for a candidate

get_candidate_profile

Get detailed information for a specific candidate

invite_candidate_to_test

Send a new test invitation to a candidate

list_assessment_candidates

List all candidates in your DevSkiller account

list_available_tests

List all assessment tests configured in your catalog

list_high_score_candidates

Identify candidates who achieved a score above a specific threshold

list_recently_sent_invitations

List test invitations sent in the last 24 hours

list_test_invitations

List all sent test invitations and their current status

search_candidates_by_identity

Search for a candidate by name or email keyword

Example Prompts for DevSkiller in Pydantic AI

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

"List all candidates who scored above 85% in recent tests."

"Show me the assessment status for candidate 'john.doe@example.com'."

"Invite 'Sarah Smith' (sarah@example.com) to the 'Frontend React' test."

Troubleshooting DevSkiller MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

DevSkiller + Pydantic AI FAQ

Common questions about integrating DevSkiller 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 DevSkiller MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.