LiftedWork MCP Server for LangChainGive LangChain instant access to 6 tools to Create Project, Create Task, List Clients, and more
LangChain is the leading Python framework for composable LLM applications. Connect LiftedWork through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
Ask AI about this App Connector for LangChain
The LiftedWork app connector for LangChain is a standout in the Productivity category — giving your AI agent 6 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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({
"liftedwork": {
"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 LiftedWork, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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 LiftedWork MCP Server
Connect your LiftedWork account to any AI agent and manage staffing through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with LiftedWork through native MCP adapters. Connect 6 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 Management — Browse candidates, inspect profiles, and track status
- Placement Tracking — Monitor active placements and contract details
- Job Listings — List open positions and their requirements
The LiftedWork MCP Server exposes 6 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.
All 6 LiftedWork tools available for LangChain
When LangChain connects to LiftedWork through Vinkius, your AI agent gets direct access to every tool listed below — spanning staffing, candidate-management, job-listings, 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.
Create a new project
Pass task data as a JSON string. Create a new task
List all clients
List all projects
List all agency tasks
List all time tracking entries
Connect LiftedWork to LangChain via MCP
Follow these steps to wire LiftedWork into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the LiftedWork MCP Server
LangChain provides unique advantages when paired with LiftedWork through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine LiftedWork 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 LiftedWork queries for multi-turn workflows
LiftedWork + LangChain Use Cases
Practical scenarios where LangChain combined with the LiftedWork MCP Server delivers measurable value.
RAG with live data: combine LiftedWork tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query LiftedWork, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain LiftedWork tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every LiftedWork tool call, measure latency, and optimize your agent's performance
Example Prompts for LiftedWork in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with LiftedWork immediately.
"Show open positions and candidate pipeline status."
"Show candidates for the Senior Developer role."
"Show active placements and contract details."
Troubleshooting LiftedWork MCP Server with LangChain
Common issues when connecting LiftedWork to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersLiftedWork + LangChain FAQ
Common questions about integrating LiftedWork MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.