# How to integrate Ayrshare MCP with Autogen ```json { "title": "How to integrate Ayrshare MCP with Autogen", "toolkit": "Ayrshare", "toolkit_slug": "ayrshare", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/ayrshare/framework/autogen", "markdown_url": "https://composio.dev/toolkits/ayrshare/framework/autogen.md", "updated_at": "2026-10-04T17:22:24.045Z" } ``` ## Introduction This guide walks you through connecting Ayrshare to AutoGen using the Composio tool router. By the end, you'll have a working Ayrshare agent that can schedule daily posts for all platforms, delete a scheduled post by its id, fetch last week's post performance data through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Ayrshare account through Composio's Ayrshare MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Ayrshare with - [Claude Code](https://composio.dev/toolkits/ayrshare/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/ayrshare/framework/claude-cowork) - [OpenAI Agents SDK](https://composio.dev/toolkits/ayrshare/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/ayrshare/framework/claude-agents-sdk) - [Codex](https://composio.dev/toolkits/ayrshare/framework/codex) - [OpenClaw](https://composio.dev/toolkits/ayrshare/framework/openclaw) - [Hermes](https://composio.dev/toolkits/ayrshare/framework/hermes-agent) - [Atomic Agent](https://composio.dev/toolkits/ayrshare/framework/atomic-agent) - [Google ADK](https://composio.dev/toolkits/ayrshare/framework/google-adk) - [LangChain](https://composio.dev/toolkits/ayrshare/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/ayrshare/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/ayrshare/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/ayrshare/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/ayrshare/framework/crew-ai) - [Pydantic AI](https://composio.dev/toolkits/ayrshare/framework/pydantic-ai) ## TL;DR Here's what you'll learn: - Get and set up your OpenAI and Composio API keys - Install the required dependencies for Autogen and Composio - Initialize Composio and create a Tool Router session for Ayrshare - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Ayrshare tools - Run a live chat loop where you ask the agent to perform Ayrshare operations ## What is AutoGen? Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows. Key features include: - Multi-Agent Systems: Build collaborative agent workflows - MCP Workbench: Native support for Model Context Protocol tools - Streaming HTTP: Connect to external services through streamable HTTP - AssistantAgent: Pre-built agent class for tool-using assistants ## What is the Ayrshare MCP server, and what's possible with it? The Ayrshare MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ayrshare account. It provides structured and secure access to your auto-post schedules, post history, performance metrics, and published posts, so your agent can create schedules, choose posting times, filter schedules by weekday, review post performance, and delete published posts on your behalf. - Auto-post schedule creation: Have your agent create new auto-post schedules for your connected social media platforms. - Custom posting times: Direct your agent to set the specific times when scheduled posts should go out. - Weekday scheduling: Let the agent limit an auto-post schedule to the days of the week you choose. - Post history and metrics: Instruct your agent to retrieve your publishing history and review the available performance metrics. - Published post deletion: Have your agent delete a previously published Ayrshare post when it is no longer needed. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `AYRSHARE_CREATE_AUTO_SCHEDULE` | Create Auto Schedule | Tool to create a new auto-post schedule with specified times and optional weekday filters. Use when setting up recurring posting plans. | | `AYRSHARE_DELETE_DELETE_POST` | Delete a previously published Ayrshare post | Tool to delete an Ayrshare post. Use when you need to remove a published or scheduled post by its Ayrshare Post ID, after confirming the correct ID. Note: Instagram and TikTok published posts cannot be deleted via API; set `mark_manual_deleted=True` or remove manually. | | `AYRSHARE_GET_POST_HISTORY` | Get Post History | Tool to retrieve Ayrshare post history with metrics. Use when you need to fetch and filter past posts by date, status, or record count. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Ayrshare MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Ayrshare. Instead of manually wiring Ayrshare APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely. 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 You will need: - A Composio API key - An OpenAI API key (used by Autogen's OpenAIChatCompletionClient) - A Ayrshare account you can connect to Composio - Some basic familiarity with Autogen and Python async ### 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 Composio, Autogen extensions, and dotenv. What's happening: - composio connects your agent to Ayrshare via MCP - autogen-agentchat provides the AssistantAgent class - autogen-ext-openai provides the OpenAI model client - autogen-ext-tools provides MCP workbench support ```bash pip install composio python-dotenv pip install autogen-agentchat autogen-ext-openai autogen-ext-tools ``` ### 3. Set up environment variables Create a .env file in your project folder. What's happening: - COMPOSIO_API_KEY is required to talk to Composio - OPENAI_API_KEY is used by Autogen's OpenAI client - USER_ID is how Composio identifies which user's Ayrshare connections to use ```bash COMPOSIO_API_KEY=your-composio-api-key OPENAI_API_KEY=your-openai-api-key USER_ID=your-user-identifier@example.com ``` ### 4. Import dependencies and create Tool Router session What's happening: - load_dotenv() reads your .env file - Composio(api_key=...) initializes the SDK - create(...) creates a Tool Router session that exposes Ayrshare tools - session.mcp.url is the MCP endpoint that Autogen will connect to ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Ayrshare session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["ayrshare"] ) url = session.mcp.url ``` ### 5. Configure MCP parameters for Autogen Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for. What's happening: - url points to the Tool Router MCP endpoint from Composio - timeout is the HTTP timeout for requests - sse_read_timeout controls how long to wait when streaming responses - terminate_on_close=True cleans up the MCP server process when the workbench is closed ```python # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) ``` ### 6. Create the model client and agent What's happening: - OpenAIChatCompletionClient wraps the OpenAI model for Autogen - McpWorkbench connects the agent to the MCP tools - AssistantAgent is configured with the Ayrshare tools from the workbench ```python # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Ayrshare assistant agent with MCP tools agent = AssistantAgent( name="ayrshare_assistant", description="An AI assistant that helps with Ayrshare operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) ``` ### 7. Run the interactive chat loop What's happening: - The script prompts you in a loop with You: - Autogen passes your input to the model, which decides which Ayrshare tools to call via MCP - agent.run_stream(...) yields streaming messages as the agent thinks and calls tools - Typing exit, quit, or bye ends the loop ```python print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Ayrshare related question or task to the agent.\n") # Conversation loop 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") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, "content") and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Ayrshare session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["ayrshare"] ) url = session.mcp.url # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Ayrshare assistant agent with MCP tools agent = AssistantAgent( name="ayrshare_assistant", description="An AI assistant that helps with Ayrshare operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Ayrshare related question or task to the agent.\n") # Conversation loop 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") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, 'content') and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You now have an Autogen assistant wired into Ayrshare through Composio's Tool Router and MCP. From here you can: - Add more toolkits to the toolkits list, for example notion or hubspot - Refine the agent description to point it at specific workflows - Wrap this script behind a UI, Slack bot, or internal tool Once the pattern is clear for Ayrshare, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Ayrshare MCP Agent with another framework - [Claude Code](https://composio.dev/toolkits/ayrshare/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/ayrshare/framework/claude-cowork) - [OpenAI Agents SDK](https://composio.dev/toolkits/ayrshare/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/ayrshare/framework/claude-agents-sdk) - [Codex](https://composio.dev/toolkits/ayrshare/framework/codex) - [OpenClaw](https://composio.dev/toolkits/ayrshare/framework/openclaw) - [Hermes](https://composio.dev/toolkits/ayrshare/framework/hermes-agent) - [Atomic Agent](https://composio.dev/toolkits/ayrshare/framework/atomic-agent) - [Google ADK](https://composio.dev/toolkits/ayrshare/framework/google-adk) - [LangChain](https://composio.dev/toolkits/ayrshare/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/ayrshare/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/ayrshare/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/ayrshare/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/ayrshare/framework/crew-ai) - [Pydantic AI](https://composio.dev/toolkits/ayrshare/framework/pydantic-ai) ## Related Toolkits - [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide. - [Instagram](https://composio.dev/toolkits/instagram) - Instagram is a social platform for sharing photos, videos, and stories with your audience. It helps brands and creators engage, grow, and analyze their online presence. - [DEV Community](https://composio.dev/toolkits/devto) - DEV Community (dev.to) is a social publishing platform for software developers. Use it to share technical articles, grow a developer audience, and join community discussions. - [Dotsimple](https://composio.dev/toolkits/dotsimple) - Dotsimple is a social media management platform for planning, creating, and publishing content. It helps teams boost their reach with AI-powered content generation and actionable analytics. - [Just One API](https://composio.dev/toolkits/just_one_api) - Just One API is a unified platform providing public social, creator, entertainment, and ecommerce data. Use it to query standardized, metered datasets across hundreds of endpoints for research and product insights. - [Pinterest](https://composio.dev/toolkits/pinterest) - Pinterest is a visual discovery platform for recipes, home ideas, style inspiration, travel plans, and more. It helps people save, organize, and revisit ideas through Pins and Boards. - [Strava](https://composio.dev/toolkits/strava) - Strava is a social fitness network and app for cyclists and runners. It's perfect for tracking workouts, sharing progress, and joining active communities. - [TikHub](https://composio.dev/toolkits/tik_hub) - TikHub is a social metadata API that exposes supported TikTok and social metadata routes. It provides consistent, API-key-based access to public metadata without cookies or device signatures. - [Tiktok](https://composio.dev/toolkits/tiktok) - Tiktok is a short-form video platform for creating, sharing, and discovering viral content. It helps creators and brands reach massive audiences with creative tools and global social features. - [Twitch](https://composio.dev/toolkits/twitch) - Twitch is a live streaming platform for gamers, creators, and communities. It enables real-time interaction, monetization, and community building. - [TwitterShots](https://composio.dev/toolkits/twittershots) - TwitterShots is an API service that renders public X posts as clean screenshots and retrieves tweet content. Use it to capture social posts, extract tweet text, and track API usage without building screenshot infrastructure. - [Upload-Post](https://composio.dev/toolkits/upload_post) - Upload-Post is a social publishing API for posting, scheduling, and managing content across social networks. Use it to run multi-channel content workflows through one clean API instead of separate platform integrations. - [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable. - [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options. - [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices. - [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management. - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure. - [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Ayrshare MCP? With a standalone Ayrshare MCP server, the agents and LLMs can only access a fixed set of Ayrshare tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Ayrshare and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Autogen? Yes, you can. Autogen 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 Ayrshare tools. ### Can I manage the permissions and scopes for Ayrshare while using Tool Router? Yes, absolutely. You can configure which Ayrshare 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 Ayrshare data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)