# How to integrate Linkedin MCP with Pydantic AI ```json { "title": "How to integrate Linkedin MCP with Pydantic AI", "toolkit": "Linkedin", "toolkit_slug": "linkedin", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/linkedin/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/linkedin/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:17:40.402Z" } ``` ## Introduction This guide walks you through connecting Linkedin to Pydantic AI using the Composio tool router. By the end, you'll have a working Linkedin agent that can share a new post about our product launch, delete your last published linkedin post, fetch company pages i can manage through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Linkedin account through Composio's Linkedin MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Linkedin with - [ChatGPT](https://composio.dev/toolkits/linkedin/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/linkedin/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/linkedin/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/linkedin/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/linkedin/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/linkedin/framework/codex) - [Cursor](https://composio.dev/toolkits/linkedin/framework/cursor) - [VS Code](https://composio.dev/toolkits/linkedin/framework/vscode) - [OpenCode](https://composio.dev/toolkits/linkedin/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/linkedin/framework/openclaw) - [Hermes](https://composio.dev/toolkits/linkedin/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/linkedin/framework/cli) - [Google ADK](https://composio.dev/toolkits/linkedin/framework/google-adk) - [LangChain](https://composio.dev/toolkits/linkedin/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/linkedin/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/linkedin/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/linkedin/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/linkedin/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up your Composio API key and User ID - How to create a Composio Tool Router session for Linkedin - How to attach an MCP Server to a Pydantic AI agent - How to stream responses and maintain chat history - How to build a simple REPL-style chat interface to test your Linkedin workflows ## What is Pydantic AI? Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications. Key features include: - Type Safety: Built on Pydantic for automatic data validation - MCP Support: Native support for Model Context Protocol servers - Streaming: Built-in support for streaming responses - Async First: Designed for async/await patterns ## What is the Linkedin MCP server, and what's possible with it? The Linkedin MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Linkedin account. It provides structured and secure access to your LinkedIn profile and company pages, so your agent can post updates, fetch your profile, manage company info, and even delete posts on your behalf. - Automated LinkedIn posting: Let your agent create and share new posts from your profile or managed company pages, keeping your network engaged without manual effort. - Profile information retrieval: Instantly fetch your LinkedIn profile details, including author ID and headline, for use in resumes, reporting, or personalized content generation. - Company page management: Retrieve a list of organizations you manage, making it easy for your agent to post or gather company info for employer branding and outreach. - Content cleanup and moderation: Direct your agent to delete specific LinkedIn posts (by share ID) to maintain a professional, up-to-date presence. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `LINKEDIN_CREATE_ARTICLE_OR_URL_SHARE` | Create article or URL share | Tool to create an article or URL share on LinkedIn using the UGC Posts API. Use when you need to share a link with optional commentary on LinkedIn. Supports sharing URLs as articles with customizable visibility settings. | | `LINKEDIN_CREATE_COMMENT_ON_POST` | Create comment on LinkedIn post | Tool to create a first-level or nested comment on a LinkedIn share, UGC post, or parent comment via the Social Actions Comments API. Use when you need to engage with posts by adding comments or replying to existing comments. Supports text comments with optional @-mentions and image attachments. | | `LINKEDIN_CREATE_LINKED_IN_POST` | Create a LinkedIn post | Creates a new post on LinkedIn for the authenticated user or an organization they manage. Requires w_member_social scope for posting as a person, and w_organization_social scope for posting as an organization (with ADMINISTRATOR, DIRECT_SPONSORED_CONTENT_POSTER, or CONTENT_ADMIN role). | | `LINKEDIN_DELETE_LINKED_IN_POST` | Delete LinkedIn Post | Deletes a specific LinkedIn post (share) by its unique `share_id`, which must correspond to an existing share. | | `LINKEDIN_DELETE_POST` | Delete Post | Delete a LinkedIn post using the Posts API REST endpoint. Supports both ugcPost and share URN formats. The endpoint is idempotent - previously deleted posts return success (204). | | `LINKEDIN_DELETE_UGC_POST` | Delete UGC Post (Legacy) | Delete a UGC post using the legacy UGC Post API endpoint. Use when you need to delete a post using the v2/ugcPosts endpoint. Deletion is idempotent - previously deleted posts also return success. | | `LINKEDIN_GET_AD_TARGETING_FACETS` | Get ad targeting facets | Tool to retrieve available ad targeting facets from LinkedIn Marketing API. Use when you need to discover what targeting options are available for ad campaigns (e.g., locations, industries, job functions). | | `LINKEDIN_GET_AUDIENCE_COUNTS` | Get audience counts | Retrieves audience size counts for specified targeting criteria. Use when estimating reach for LinkedIn ad campaigns or targeted content. | | `LINKEDIN_GET_COMPANY_INFO` | Get company info | Retrieves organizations where the authenticated user has specific roles (ACLs), to determine their management or content posting capabilities for LinkedIn company pages. | | `LINKEDIN_GET_IMAGE` | Get image details | Tool to retrieve details of a LinkedIn image using its URN. Use when you need to check image status, get download URLs, or access image metadata for a single image. | | `LINKEDIN_GET_IMAGES` | Get images | Tool to retrieve image metadata including download URLs, status, and dimensions from LinkedIn's Images API. Use when you need to access image details for posts, profiles, or media library assets. | | `LINKEDIN_GET_MY_INFO` | Get my info | Fetches the authenticated LinkedIn user's profile information including name, headline, profile picture, and other profile details. | | `LINKEDIN_GET_NETWORK_SIZE` | Get network size | Tool to retrieve the follower count for a LinkedIn organization. Use when you need to get the number of members following a specific company or organization on LinkedIn. | | `LINKEDIN_GET_ORG_PAGE_STATS` | Get organization page statistics | Tool to retrieve page statistics for a LinkedIn organization page. Use when you need engagement metrics like page views and custom button clicks. Supports both lifetime statistics (all-time data segmented by demographics) and time-bound statistics (aggregate data for specific time ranges). Requires rw_organization_admin permission with ADMINISTRATOR role for the organization. | | `LINKEDIN_GET_PERSON` | Get person profile | Retrieves a LinkedIn member's profile information by their person ID. Returns lite profile fields (name, profile picture) by default, or basic profile fields (including headline and vanity name) with appropriate permissions. | | `LINKEDIN_GET_POST_CONTENT` | Get post content | Tool to retrieve detailed post content including text, images, videos, and metadata from LinkedIn by post URN. Use when you need to fetch the full content and details of a specific LinkedIn post. | | `LINKEDIN_GET_SHARE_STATS` | Get share statistics | Retrieves share statistics for a LinkedIn organization, including impressions, clicks, likes, comments, and shares. Use to analyze content performance for an organization page. Optionally filter by time intervals to get time-bound statistics. | | `LINKEDIN_GET_VIDEOS` | Get videos | Retrieves video metadata from LinkedIn Marketing API. Supports single video retrieval, batch retrieval (multiple videos), and finding videos by associated account with pagination. Use when you need to get video details including duration, dimensions, status, download URLs, and media library information. | | `LINKEDIN_INITIALIZE_IMAGE_UPLOAD` | Initialize image upload | Tool to initialize an image upload to LinkedIn and return a presigned upload URL plus the resulting image URN. Use when you need to prepare an image upload for LinkedIn posts. After calling this tool, upload the image bytes to the returned upload_url via PUT request, then use the image URN in CREATE_LINKED_IN_POST action. | | `LINKEDIN_LIST_REACTIONS` | List reactions on entity | Retrieves reactions (likes, celebrations, etc.) on a LinkedIn entity such as a share, post, or comment. Use when you need to see who reacted to content and what type of reactions were used. | | `LINKEDIN_REGISTER_IMAGE_UPLOAD` | Register image upload | Tool to initialize a native LinkedIn image upload for feed shares and return a presigned upload URL plus the resulting digital media asset URN. Use when you need to upload an image to attach to a LinkedIn post. After calling this tool, upload the image bytes to the returned upload_url, then use the asset_urn in LINKEDIN_CREATE_LINKED_IN_POST. | | `LINKEDIN_SEARCH_AD_TARGETING_ENTITIES` | Search ad targeting entities | Search for ad targeting entities using typeahead search. Use when you need to find targeting entities like geographic locations, job titles, industries, or other targeting criteria for LinkedIn ad campaigns. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Linkedin MCP server is an implementation of the Model Context Protocol that connects your AI agent to Linkedin. It provides structured and secure access so your agent can perform Linkedin operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before starting, make sure you have: - Python 3.9 or higher - A Composio account with an active API key - Basic familiarity with Python and async programming ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install dependencies Install the required libraries. What's happening: - composio connects your agent to external SaaS tools like Linkedin - pydantic-ai lets you create structured AI agents with tool support - python-dotenv loads your environment variables securely from a .env file ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your agent to Composio's API - USER_ID associates your session with your account for secure tool access - OPENAI_API_KEY to access OpenAI LLMs ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies What's happening: - We load environment variables and import required modules - Composio manages connections to Linkedin - MCPServerStreamableHTTP connects to the Linkedin MCP server endpoint - Agent from Pydantic AI lets you define and run the AI assistant ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() ``` ### 5. Create a Tool Router Session What's happening: - We're creating a Tool Router session that gives your agent access to Linkedin tools - The create method takes the user ID and specifies which toolkits should be available - The returned session.mcp.url is the MCP server URL that your agent will use ```python async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Linkedin composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["linkedin"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") ``` ### 6. Initialize the Pydantic AI Agent What's happening: - The MCP client connects to the Linkedin endpoint - The agent uses GPT-5 to interpret user commands and perform Linkedin operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent linkedin_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[linkedin_mcp], instructions=( "You are a Linkedin assistant. Use Linkedin tools to help users " "with their requests. Ask clarifying questions when needed." ), ) ``` ### 7. Build the chat interface What's happening: - The agent reads input from the terminal and streams its response - Linkedin API calls happen automatically under the hood - The model keeps conversation history to maintain context across turns ```python # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Linkedin.\n") while True: user_input = input("You: ").strip() if user_input.lower() in {"exit", "quit", "bye"}: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Linkedin composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["linkedin"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") # Attach the MCP server to a Pydantic AI Agent linkedin_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[linkedin_mcp], instructions=( "You are a Linkedin assistant. Use Linkedin tools to help users " "with their requests. Ask clarifying questions when needed." ), ) # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Linkedin.\n") while True: user_input = input("You: ").strip() if user_input.lower() in {"exit", "quit", "bye"}: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You've built a Pydantic AI agent that can interact with Linkedin through Composio's Tool Router. With this setup, your agent can perform real Linkedin actions through natural language. You can extend this further by: - Adding other toolkits like Gmail, HubSpot, or Salesforce - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Linkedin for workflow automation) This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations. ## How to build Linkedin MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/linkedin/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/linkedin/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/linkedin/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/linkedin/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/linkedin/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/linkedin/framework/codex) - [Cursor](https://composio.dev/toolkits/linkedin/framework/cursor) - [VS Code](https://composio.dev/toolkits/linkedin/framework/vscode) - [OpenCode](https://composio.dev/toolkits/linkedin/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/linkedin/framework/openclaw) - [Hermes](https://composio.dev/toolkits/linkedin/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/linkedin/framework/cli) - [Google ADK](https://composio.dev/toolkits/linkedin/framework/google-adk) - [LangChain](https://composio.dev/toolkits/linkedin/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/linkedin/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/linkedin/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/linkedin/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/linkedin/framework/crew-ai) ## Related Toolkits - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. - [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic. - [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns. - [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active. - [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place. - [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES. - [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere. - [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools. - [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools. - [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. - [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals. - [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams. - [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience. - [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs. - [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics. - [Doppler marketing automation](https://composio.dev/toolkits/doppler_marketing_automation) - Doppler marketing automation is a platform for creating, sending, and tracking email campaigns. It helps you automate marketing workflows and manage subscriber lists for better engagement. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Linkedin MCP? With a standalone Linkedin MCP server, the agents and LLMs can only access a fixed set of Linkedin tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Linkedin and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Pydantic AI? Yes, you can. Pydantic AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Linkedin tools. ### Can I manage the permissions and scopes for Linkedin while using Tool Router? Yes, absolutely. You can configure which Linkedin scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do. ### How safe is my data with Composio Tool Router? All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Linkedin data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)