LiftedWork MCP Server for Pydantic AIGive Pydantic AI instant access to 6 tools to Create Project, Create Task, List Clients, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect LiftedWork 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 LiftedWork app connector for Pydantic AI 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 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 LiftedWork "
"(6 tools)."
),
)
result = await agent.run(
"What tools are available in LiftedWork?"
)
print(result.data)
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.
Pydantic AI validates every LiftedWork tool response against typed schemas, catching data inconsistencies at build time. Connect 6 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 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 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 6 LiftedWork tools available for Pydantic AI
When Pydantic AI 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 Pydantic AI via MCP
Follow these steps to wire LiftedWork into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the LiftedWork MCP Server
Pydantic AI provides unique advantages when paired with LiftedWork 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 LiftedWork integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your LiftedWork connection logic from agent behavior for testable, maintainable code
LiftedWork + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the LiftedWork MCP Server delivers measurable value.
Type-safe data pipelines: query LiftedWork with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple LiftedWork tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query LiftedWork and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock LiftedWork responses and write comprehensive agent tests
Example Prompts for LiftedWork in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI
Common issues when connecting LiftedWork to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiLiftedWork + Pydantic AI FAQ
Common questions about integrating LiftedWork MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.