Which scopes are required to post as an organization?

Your access token must include `w_organization_social` to create posts and comments, and `r_organization_social` to list them.

How do I find my Organization ID?

Use the `list_managed_pages` tool. It will return all organizations where you have management roles along with their unique IDs.

Can I reply to a specific comment?

The current version supports creating top-level comments on posts. Support for threaded replies (using the `parent` field) is handled via the same comment tool by providing the parent URN if supported by the engine.

LinkedIn Page Management MCP Server for Pydantic AI 7 tools — connect in under 2 minutes

Name: LinkedIn Page Management
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 7 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect LinkedIn Page Management through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 LinkedIn Page Management "
            "(7 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in LinkedIn Page Management?"
    )
    print(result.data)

asyncio.run(main())

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* 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 Page Management MCP Server

Connect your LinkedIn Company Page to any AI agent to automate your social media management and community engagement. This MCP server enables your agent to list managed organizations, publish new posts, moderate comments, and track social reactions directly from natural language interfaces.

Pydantic AI validates every LinkedIn Page Management tool response against typed schemas, catching data inconsistencies at build time. Connect 7 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

Post Automation — Publish text-based updates and commentary directly to your Company Page feed
Community Moderation — List and retrieve comments on any post to stay engaged with your audience
Response Management — Post official comments and replies on behalf of your organization to foster discussion
Social Analytics — List likes and reactions on specific posts to monitor engagement trends
Content Maintenance — Retrieve a history of organization posts and permanently remove outdated content
Organization Oversight — Identify all pages where the authenticated user has management roles and ACLs

The LinkedIn Page Management MCP Server exposes 7 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.

How to Connect LinkedIn Page Management to Pydantic AI via MCP

Follow these steps to integrate the LinkedIn Page Management MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 7 tools from LinkedIn Page Management with type-safe schemas

Why Use Pydantic AI with the LinkedIn Page Management MCP Server

Pydantic AI provides unique advantages when paired with LinkedIn Page Management 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 LinkedIn Page Management integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your LinkedIn Page Management connection logic from agent behavior for testable, maintainable code

LinkedIn Page Management + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the LinkedIn Page Management MCP Server delivers measurable value.

Type-safe data pipelines: query LinkedIn Page Management with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple LinkedIn Page Management tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query LinkedIn Page Management and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock LinkedIn Page Management responses and write comprehensive agent tests

LinkedIn Page Management MCP Tools for Pydantic AI (7)

These 7 tools become available when you connect LinkedIn Page Management to Pydantic AI via MCP:

create_page_post

Create a new post on a Company Page

create_post_comment

Add a comment to a post as the organization

delete_page_post

Delete a specific post

list_managed_pages

Use this to find organization IDs. List all LinkedIn Company Pages managed by the user

list_page_posts

List recent posts from a Company Page

list_post_comments

List all comments on a specific post

list_post_likes

List likes/reactions on a specific post

Example Prompts for LinkedIn Page Management in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with LinkedIn Page Management immediately.

"List all LinkedIn Company Pages I manage."

"Create a new post on page '12345' with the text 'Welcome to our weekly update!'."

"Show comments for the post 'urn:li:share:987654321'."

Troubleshooting LinkedIn Page Management MCP Server with Pydantic AI

Common issues when connecting LinkedIn Page Management to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

LinkedIn Page Management + Pydantic AI FAQ

Common questions about integrating LinkedIn Page Management MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your LinkedIn Page Management MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.