How to Use the CATS ATS MCP in LangChain

Q: How do I connect CATS ATS to LangChain?

Install the langchain-mcp-adapters package first. Then initialize a MultiServerMCPClient pointing to your Vinkius endpoint. Call client.gettools() and pass them to your ReAct agent.

Q: Can LangChain agents chain multiple CATS ATS MCP Server tools?

Yes. A common pattern is calling listrecruitmentcompanies to find a client, then passing that ID into listrecruitmentcontacts. The output of one tool feeds directly into the next.

Build recruitment reasoning pipelines in LangChain by connecting the CATS ATS MCP Server directly to your agents.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect CATS ATS MCP to LangChain

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

GDPR Free for Subscribers

Setup CATS ATS with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Candidate Sourcing Pipelines

`search_candidates` lets your LangChain agent pull specific applicant profiles based on custom filters. You pass the criteria, and the tool returns structured data ready for the next step in your chain. Feed those results straight into `get_candidate_details` to extract full resumes and contact info. Your ReAct agent decides exactly which profiles need deeper inspection before passing the final list to a hiring manager.

Job Order Aggregation via MCP

`list_job_orders` gives your pipeline immediate access to open positions and their requirements. LangChain reads this array and maps it against available talent pools. Combine this with `get_job_details` to build an automated matching system. The agent pulls the job specs, queries your vector store for matching skills, and outputs a ranked shortlist of candidates.

Recruitment Activity Chains

`list_recruitment_activities` exposes recent notes and status changes across your hiring pipeline. Your agent parses these logs to figure out who needs a follow-up email today. Hook this up to LangSmith tracing to watch exactly how your agent interprets recruiter notes. You see the exact token usage and latency every time the system checks for stalled applications.

Setup guide

Set up CATS ATS MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes CATS ATS tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

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

async with MultiServerMCPClient({
    "cats-ats-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent CATS ATS transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by CATS ATS. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect CATS ATS now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about CATS ATS MCP in LangChain

Install the `langchain-mcp-adapters` package first. Then initialize a `MultiServerMCPClient` pointing to your Vinkius endpoint. Call `client.get_tools()` and pass them to your ReAct agent.

Yes. A common pattern is calling `list_recruitment_companies` to find a client, then passing that ID into `list_recruitment_contacts`. The output of one tool feeds directly into the next.

It tracks everything. You get full visibility into the inputs sent to the ATS and the JSON returned. This makes debugging complex candidate searches much easier.

Pagination is built into the tool schema. Your agent will read the response metadata and request the next batch if it hits a limit.

Vinkius runs the ATS integration inside a zero-trust V8 Isolate Sandbox. Resumes, contact details, and interview notes only exist in memory during the request. The container dies the second your agent finishes pulling the data.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript