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 LangChain 10 tools — connect in under 2 minutes

Name: DevSkiller
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect DevSkiller through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "devskiller": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using DevSkiller, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

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 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.

LangChain's ecosystem of 500+ components combines seamlessly with DevSkiller through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the DevSkiller MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from DevSkiller via MCP

Why Use LangChain with the DevSkiller MCP Server

LangChain provides unique advantages when paired with DevSkiller through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine DevSkiller MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across DevSkiller queries for multi-turn workflows

DevSkiller + LangChain Use Cases

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

RAG with live data: combine DevSkiller tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query DevSkiller, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain DevSkiller tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every DevSkiller tool call, measure latency, and optimize your agent's performance

DevSkiller MCP Tools for LangChain (10)

These 10 tools become available when you connect DevSkiller to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

DevSkiller + LangChain FAQ

Common questions about integrating DevSkiller MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.