LinkedIn MCP Server for OpenAI Agents SDK 6 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect LinkedIn 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="LinkedIn Assistant",
instructions=(
"You help users interact with LinkedIn. "
"You have access to 6 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from LinkedIn"
)
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 LinkedIn MCP Server
Empower your AI agent to orchestrate your entire professional ecosystem on LinkedIn, the world's largest professional network. By connecting LinkedIn to your agent, you transform professional networking and publishing into a natural conversation. Your agent can instantly list your administered organizations, audit recent posts, and create new content without you ever touching a dashboard. Whether you are building a personal brand or managing a corporate page, your agent acts as a real-time professional assistant, ensuring your presence is always active and your networking data is organized.
The OpenAI Agents SDK auto-discovers all 6 tools from LinkedIn through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries LinkedIn, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- Post Distribution — Create and publish new posts (UGC) directly to your profile or administered organization pages.
- Organization Oversight — List all organizations where you have administrative access and retrieve detailed metadata.
- Content Auditing — Query recent posts for any author URN to stay on top of your content strategy and engagement.
- Profile Intelligence — Retrieve detailed authenticated user info and primary email to ensure organizational alignment.
- URN Management — Quickly identify unique identifiers (URNs) for people and organizations to facilitate precise API operations.
The LinkedIn MCP Server exposes 6 tools through the Vinkius. Connect it to OpenAI Agents SDK 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 LinkedIn to OpenAI Agents SDK via MCP
Follow these steps to integrate the LinkedIn 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 6 tools from LinkedIn
Why Use OpenAI Agents SDK with the LinkedIn MCP Server
OpenAI Agents SDK provides unique advantages when paired with LinkedIn 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
LinkedIn + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the LinkedIn MCP Server delivers measurable value.
Automated workflows: build agents that query LinkedIn, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries LinkedIn, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through LinkedIn tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query LinkedIn to resolve tickets, look up records, and update statuses without human intervention
LinkedIn MCP Tools for OpenAI Agents SDK (6)
These 6 tools become available when you connect LinkedIn to OpenAI Agents SDK via MCP:
create_post
Create a new post (UGC) on LinkedIn
get_email
Get primary email address of the authenticated user
get_me
Get authenticated user info from LinkedIn
get_organization
Get details for a specific organization
list_organizations
List organizations where the user is an administrator
list_posts
List recent posts for an author
Example Prompts for LinkedIn in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with LinkedIn immediately.
"Get my LinkedIn profile and email."
"List all organizations I manage on LinkedIn."
"Create a public post on my profile: 'Excited to launch our new MCP servers!'"
Troubleshooting LinkedIn MCP Server with OpenAI Agents SDK
Common issues when connecting LinkedIn to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
LinkedIn + OpenAI Agents SDK FAQ
Common questions about integrating LinkedIn 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 LinkedIn with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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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 LinkedIn to OpenAI Agents SDK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.