How do I get my LinkedIn Ads API credentials?

1. Go to **developer.linkedin.com** and log in with your LinkedIn account. 2. Click **My Apps** → **Create App**. 3. Fill in your app name, company LinkedIn page, and logo. 4. Under the **Products** tab, request access to **Marketing Developer Platform**. 5. After approval, go to the **Auth** tab and copy your **Client ID** and **Client Secret**. 6. Paste both values below. ⚠️ Access to the Marketing API requires approval from LinkedIn (typically 1-5 business days).

Can I download lead gen form submissions?

Yes. Your AI agent can pull all lead gen form submissions including names, emails, job titles, and custom fields — ready to sync to your CRM or outreach tool.

What targeting criteria can I use?

LinkedIn offers the most precise B2B targeting: job title, job function, seniority, company name, company size, industry, skills, education, and matched audiences (ABM lists, retargeting, lookalikes).

Can I track cost-per-lead (CPL)?

Yes. Your AI agent calculates CPL by dividing total spend by leads generated — broken down by campaign, ad group, or creative. Essential for B2B marketers optimizing demand gen budgets.

LinkedIn Ads MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: LinkedIn Ads
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect LinkedIn Ads 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 Ads "
            "(8 tools)."
        ),
    )

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

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Ads MCP Server

Connect LinkedIn Ads to your AI agent and manage your B2B advertising campaigns conversationally.

Pydantic AI validates every LinkedIn Ads tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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

Campaign Management — List, create, update, and pause campaigns, campaign groups, and creatives.
B2B Analytics — Pull impressions, clicks, CTR, CPC, leads, and cost-per-lead metrics.
Audience Targeting — Query targeting by job title, company, industry, seniority, and matched audiences.
Lead Gen Forms — Access lead gen form submissions and sync leads to your CRM.

The LinkedIn Ads MCP Server exposes 8 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 Ads to Pydantic AI via MCP

Follow these steps to integrate the LinkedIn Ads 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 8 tools from LinkedIn Ads with type-safe schemas

Why Use Pydantic AI with the LinkedIn Ads MCP Server

Pydantic AI provides unique advantages when paired with LinkedIn Ads 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 Ads 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 Ads connection logic from agent behavior for testable, maintainable code

LinkedIn Ads + Pydantic AI Use Cases

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

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

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

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

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

LinkedIn Ads MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect LinkedIn Ads to Pydantic AI via MCP:

enable_campaign

Enable campaign

get_account_analytics

Get account analytics

get_account_info

Get ad account info

get_campaign_analytics

Get campaign analytics

list_campaign_groups

List campaign groups

list_campaigns

List campaigns

list_creatives

List ad creatives

pause_campaign

Pause campaign

Example Prompts for LinkedIn Ads in Pydantic AI

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

"How are my LinkedIn campaigns performing this month?"

"Download all leads from my 'CTO Retargeting' campaign."

"Increase the daily budget on 'Brand Awareness' campaign to $200."

Troubleshooting LinkedIn Ads MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

LinkedIn Ads + Pydantic AI FAQ

Common questions about integrating LinkedIn Ads 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 Ads MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.