Lancerkit MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Lancerkit through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Lancerkit Assistant",
instructions=(
"You help users interact with Lancerkit. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Lancerkit"
)
print(result.final_output)
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 Lancerkit MCP Server
Connect Lancerkit to any AI agent via MCP.
How to Connect Lancerkit to OpenAI Agents SDK via MCP
Follow these steps to integrate the Lancerkit MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 10 tools from Lancerkit
Why Use OpenAI Agents SDK with the Lancerkit MCP Server
OpenAI Agents SDK provides unique advantages when paired with Lancerkit through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Lancerkit + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Lancerkit MCP Server delivers measurable value.
Automated workflows: build agents that query Lancerkit, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Lancerkit, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Lancerkit tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Lancerkit to resolve tickets, look up records, and update statuses without human intervention
Lancerkit MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect Lancerkit to OpenAI Agents SDK via MCP:
get_client
Retrieve specific metadata of one single client
get_invoice
Retrieve data, payments, and billings for a specific invoice string ID
get_project
Get a single project details by ID
get_status
Examine account and integration connection status overall
get_time_logs
Check the recorded time logs for hours spent
list_clients
List all clients associated with the workspace
list_invoices
Fetch global invoice pipeline statistics
list_projects
List all standard projects
list_services
Fetch all specific billable service items configured online
list_tasks
Check current working tasks
Example Prompts for Lancerkit in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Lancerkit immediately.
"Draft an invoice for the Acme Corp redesign project."
"How many billable hours have I tracked this week?"
"Create a new project named Mobile App Development for Delta Tech."
Troubleshooting Lancerkit MCP Server with OpenAI Agents SDK
Common issues when connecting Lancerkit to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Lancerkit + OpenAI Agents SDK FAQ
Common questions about integrating Lancerkit MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Lancerkit with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Lancerkit to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.