# How to integrate Imagekit io MCP with Autogen ```json { "title": "How to integrate Imagekit io MCP with Autogen", "toolkit": "Imagekit io", "toolkit_slug": "imagekit_io", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/imagekit_io/framework/autogen", "markdown_url": "https://composio.dev/toolkits/imagekit_io/framework/autogen.md", "updated_at": "2026-05-12T10:15:42.675Z" } ``` ## Introduction This guide walks you through connecting Imagekit io to AutoGen using the Composio tool router. By the end, you'll have a working Imagekit io agent that can move all event photos to new 2024 folder, delete outdated logo file from media library, create custom metadata field for copyright info through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Imagekit io account through Composio's Imagekit io MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Imagekit io with - [OpenAI Agents SDK](https://composio.dev/toolkits/imagekit_io/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/imagekit_io/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/imagekit_io/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/imagekit_io/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/imagekit_io/framework/codex) - [OpenClaw](https://composio.dev/toolkits/imagekit_io/framework/openclaw) - [Hermes](https://composio.dev/toolkits/imagekit_io/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/imagekit_io/framework/cli) - [Google ADK](https://composio.dev/toolkits/imagekit_io/framework/google-adk) - [LangChain](https://composio.dev/toolkits/imagekit_io/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/imagekit_io/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/imagekit_io/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/imagekit_io/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/imagekit_io/framework/crew-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 Imagekit io - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Imagekit io tools - Run a live chat loop where you ask the agent to perform Imagekit io 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 Imagekit io MCP server, and what's possible with it? The Imagekit io MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your ImageKit.io account. It provides structured and secure access to your media library, so your agent can perform actions like organizing folders, managing files, handling bulk operations, editing metadata, and cleaning up assets on your behalf. - Bulk file operations: Effortlessly move, copy, or update tags on multiple files at once to streamline large-scale asset management. - Folder organization and management: Ask your agent to create new folders for better asset structuring or delete old folders—including all their contents—when you need to tidy up. - Custom metadata control: Let your agent create or delete custom metadata fields, so your media assets stay rich with the information your workflows need. - File and version cleanup: Instruct the agent to permanently delete files or remove outdated file versions to keep your storage lean and organized. - Bulk job monitoring: Have your agent track the status of ongoing bulk jobs, like folder copies or moves, so you always know what’s happening behind the scenes. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `IMAGEKIT_IO_BULK_JOB_STATUS` | Bulk Job Status | Retrieve the status of a bulk folder operation. Use this tool to monitor the progress of asynchronous Copy Folder or Move Folder operations by providing the jobId returned from those operations. | | `IMAGEKIT_IO_BULK_MOVE_FILES` | Bulk Move Files | Tool to move multiple files in bulk. Use when you need to relocate up to 100 ImageKit files to a specified folder in one API call. | | `IMAGEKIT_IO_BULK_REMOVE_TAGS` | Bulk Remove Tags | Tool to remove tags from multiple files in bulk. Use when you need to strip specified tags from up to 50 existing files in one API call. | | `IMAGEKIT_IO_COPY_FOLDER` | Copy Folder | Initiate an asynchronous bulk copy of a folder and all its contents to a new location. Use this tool when you need to: - Duplicate an entire folder structure including all nested files and subfolders - Create a backup of a folder at a different location - Copy a folder with or without file version history This is an asynchronous operation that returns immediately with a job ID. The actual copy happens in the background. Use IMAGEKIT_IO_BULK_JOB_STATUS with the returned jobId to check when the operation completes. Note: If a folder with the same name exists at the destination, permissions from the existing destination folder will be preserved. | | `IMAGEKIT_IO_CREATE_CUSTOM_METADATA_FIELD` | Create Custom Metadata Field | Create a new custom metadata field in ImageKit DAM. Use this tool to define custom metadata fields that can be attached to assets (images, videos, etc.) in your ImageKit media library. Once created, you can assign values to these fields on individual assets for better organization and searchability. Supported field types: - Text/Textarea: For string values with optional length constraints - Number: For numeric values with optional min/max constraints - Date: For ISO8601 date strings with optional date range constraints - Boolean: For true/false values - SingleSelect/MultiSelect: For predefined options (requires selectOptions) Note: Field names must be unique across all fields (including deleted ones). Field types cannot be changed after creation. | | `IMAGEKIT_IO_CREATE_FOLDER` | Create Folder | Creates a new folder in ImageKit.io media library. Use this to organize assets into structured folder hierarchies. The folder will be created at the specified parent path. If the parent folder doesn't exist, the API will return an error. | | `IMAGEKIT_IO_DELETE_CUSTOM_METADATA_FIELD` | Delete Custom Metadata Field | Permanently deletes a custom metadata field from ImageKit. This action is irreversible. Note: Even after deletion, you cannot create a new field with the same name. Use 'List Custom Metadata Fields' first to get the field ID if needed. Rate limit: 5 requests/second for custom metadata field operations. | | `IMAGEKIT_IO_DELETE_FILE` | Delete File | Permanently deletes a file from ImageKit by its unique file ID. WARNING: This action is irreversible. The file and all its versions will be permanently removed. Note: Cached versions of the file may still be served until the cache expires. Use the purge cache endpoint if immediate removal from CDN is required. Use this tool when you need to: - Remove unwanted or obsolete files from the media library - Clean up test uploads - Delete files that should no longer be accessible The file ID can be obtained from the 'List and Search Assets' or 'Upload File' actions. | | `IMAGEKIT_IO_DELETE_FILE_VERSION` | Delete File Version | Permanently deletes a specific non-current file version from ImageKit.io. Use this when you need to remove an older version of a file while keeping the current version intact. Note: This action is irreversible. To delete all versions of a file, use the Delete File action instead. | | `IMAGEKIT_IO_DELETE_FOLDER` | Delete Folder | Permanently delete a folder and all its contents from ImageKit Media Library. WARNING: This is a destructive operation that cannot be undone. All files and subfolders within the specified folder will be permanently removed. Use this when you need to: - Remove an entire folder structure - Clean up unused folders - Delete test/temporary folders The operation is idempotent - deleting a non-existent folder will not raise an error. | | `IMAGEKIT_IO_DELETE_MULTIPLE_FILES` | Delete Multiple Files | Permanently delete multiple files from ImageKit media library in a single batch operation. Use this tool when you need to: - Remove up to 100 files at once by their unique file IDs - Clean up unused assets from your media library - Bulk delete files after migration or reorganization Important notes: - Deletion is permanent and includes all file versions - Cached CDN responses are NOT automatically purged (use Purge Cache action if needed) - File IDs can be obtained from 'List and Search Assets' or upload responses Returns the list of successfully deleted file IDs. On partial success (some files deleted, some failed), also returns an errors array with per-file failure details. | | `IMAGEKIT_IO_GET_AUTHENTICATION_PARAMETERS` | Get Upload Authentication Parameters | Tool to generate authentication parameters for client-side file uploads. Use when preparing client-side uploads. | | `IMAGEKIT_IO_GET_FILE_DETAILS` | Get File Details | Tool to retrieve details of a specific file. Use after uploading or listing assets to get full metadata. | | `IMAGEKIT_IO_GET_FILE_METADATA` | Get File Metadata | Tool to retrieve metadata of an uploaded file. Use after confirming a successful upload to get EXIF, pHash, dimensions, and other image metadata. | | `IMAGEKIT_IO_GET_FILE_VERSION_DETAILS` | Get File Version Details | Tool to retrieve details of a specific file version. Use after listing or uploading assets when you need to inspect version metadata. | | `IMAGEKIT_IO_GET_USAGE` | Get Usage | Retrieve ImageKit account usage metrics for a specified date range. Returns bandwidth consumption and media library storage usage. The response includes data from startDate up to (but not including) endDate. Maximum allowed date range is 90 days. | | `IMAGEKIT_IO_LIST_AND_SEARCH_ASSETS` | List and Search Media Assets | List and search media assets (files, folders, file-versions) in your ImageKit media library. Use this tool to: - Browse all assets with optional pagination (limit/skip) - Filter by type (file, folder, file-version, or all) - Filter by name, tags, or file type (image/non-image) - Search with advanced Lucene-style queries (e.g., 'size > 1000000 AND tags IN ["banner"]') - Sort results by name, date, size, or dimensions Returns a list of asset objects with metadata including URLs, dimensions, tags, and timestamps. | | `IMAGEKIT_IO_LIST_CUSTOM_METADATA_FIELDS` | List Custom Metadata Fields | List all custom metadata fields defined in the ImageKit Media Library. Use this tool to: - Retrieve all metadata field definitions (name, label, type, constraints) - Get field IDs required for updating or deleting fields - View field configurations (required, default values, select options) - Include soft-deleted fields when needed for auditing | | `IMAGEKIT_IO_LIST_FILE_VERSIONS` | List File Versions | Retrieves all versions of a specific file in ImageKit. Returns a list of file version objects including metadata like version ID, creation date, and publication status. Use this to view file history, compare versions, or find a specific version to restore. Requires a valid fileId which can be obtained from the List Assets API or Upload API response. | | `IMAGEKIT_IO_MOVE_FOLDER` | Move Folder | Move a folder from one location to another in your ImageKit media library. This operation is asynchronous - it returns a jobId immediately, and the actual move happens in the background. The folder will be moved to become a subfolder of the destination path. Use IMAGEKIT_IO_BULK_JOB_STATUS with the returned jobId to check if the move has completed. Example: Moving '/photos/summer' to '/archive' will result in '/archive/summer'. | | `IMAGEKIT_IO_PURGE_CACHE` | Purge ImageKit Cache | Purge CDN and ImageKit internal caches for a specific URL or URL pattern. Use this action when you need to: - Invalidate cached content after updating an image - Force CDN to fetch the latest version of a file - Clear cache for a directory using wildcard (*) Note: Cache purging is asynchronous. Use the returned requestId with IMAGEKIT_IO_PURGE_STATUS to check completion. Monthly purge limits apply based on your pricing plan (typically 1000 URLs/month). | | `IMAGEKIT_IO_PURGE_STATUS` | Check purge cache status | Tool to check the status of a cache purge request. Use after initiating a purge to retrieve its current state. Example: "What's the status of purge request id abc123?" | | `IMAGEKIT_IO_RENAME_FILE` | Rename File | Renames an existing file in the ImageKit media library. Use this action when you need to change a file's name. Important: Old URLs will stop working after rename (unless CDN cache is active). This operation renames all file versions. Set purgeCache=True to clear CDN cached content for the old URL. Returns 404 if file not found, 409 if a file with the new name already exists in the same folder. | | `IMAGEKIT_IO_RESTORE_FILE_VERSION` | Restore File Version | Restores a non-current file version to become the current version in ImageKit. Use this to revert a file to a previous state. First use the List File Versions API to find the versionId of the version you want to restore. | | `IMAGEKIT_IO_UPDATE_CUSTOM_METADATA_FIELD` | Update Custom Metadata Field | Updates an existing custom metadata field's label or schema constraints in ImageKit DAM. Use this to: - Change the display label of a metadata field - Update validation constraints (min/max values, min/max length) - Set or modify the default value - Change whether the field is required Note: The field type and name cannot be changed after creation. At least one of 'label' or 'schema' must be provided in the request. | | `IMAGEKIT_IO_UPDATE_FILE_DETAILS` | Update File Details | Update file details in ImageKit media library. Use this tool to modify tags, custom coordinates, custom metadata, AI tags, apply extensions (like background removal), or change publication status. Note: When updating publication status via 'publish', no other parameters can be included in the request. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Imagekit io MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Imagekit io. Instead of manually wiring Imagekit io 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 Imagekit io 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 Imagekit io 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 Imagekit io 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 Imagekit io 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 Imagekit io session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["imagekit_io"] ) 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 Imagekit io 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 Imagekit io assistant agent with MCP tools agent = AssistantAgent( name="imagekit_io_assistant", description="An AI assistant that helps with Imagekit io 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 Imagekit io 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 Imagekit io 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 Imagekit io session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["imagekit_io"] ) 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 Imagekit io assistant agent with MCP tools agent = AssistantAgent( name="imagekit_io_assistant", description="An AI assistant that helps with Imagekit io 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 Imagekit io 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 Imagekit io 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 Imagekit io, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Imagekit io MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/imagekit_io/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/imagekit_io/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/imagekit_io/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/imagekit_io/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/imagekit_io/framework/codex) - [OpenClaw](https://composio.dev/toolkits/imagekit_io/framework/openclaw) - [Hermes](https://composio.dev/toolkits/imagekit_io/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/imagekit_io/framework/cli) - [Google ADK](https://composio.dev/toolkits/imagekit_io/framework/google-adk) - [LangChain](https://composio.dev/toolkits/imagekit_io/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/imagekit_io/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/imagekit_io/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/imagekit_io/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/imagekit_io/framework/crew-ai) ## Related Toolkits - [Youtube](https://composio.dev/toolkits/youtube) - YouTube is a leading video-sharing platform for uploading, streaming, and discovering content. It empowers creators and businesses to reach global audiences and monetize their work. - [Amara](https://composio.dev/toolkits/amara) - Amara is a collaborative platform for creating and managing subtitles and captions for videos. It helps make content accessible and multilingual for global audiences. - [Cats](https://composio.dev/toolkits/cats) - Cats is an API with a huge library of cat images, breed data, and cat facts. It makes finding adorable cat photos and trivia effortless for your apps and users. - [Chatfai](https://composio.dev/toolkits/chatfai) - Chatfai is an AI platform that lets users talk to AI versions of fictional characters from books, movies, and games. It offers an engaging, interactive experience for fans to chat, roleplay, and explore creative dialogues. - [Cincopa](https://composio.dev/toolkits/cincopa) - Cincopa is a multimedia platform for uploading, managing, and customizing videos, images, and audio. It helps you deliver engaging media experiences with robust APIs and flexible integrations. - [Dungeon fighter online](https://composio.dev/toolkits/dungeon_fighter_online) - Dungeon Fighter Online (DFO) is an arcade-style, side-scrolling action RPG packed with dynamic combat and progression. Play solo or with friends to battle monsters, complete quests, and upgrade your characters. - [Elevenlabs](https://composio.dev/toolkits/elevenlabs) - Elevenlabs is an advanced AI voice generation platform for lifelike, multilingual speech synthesis. Perfect for creating natural voices for videos, apps, and business content in seconds. - [Elevenreader](https://composio.dev/toolkits/elevenreader) - Elevenreader is an AI-powered text-to-speech service by ElevenLabs that converts written content into lifelike audio. It enables fast, natural audio generation from any text. - [Epic games](https://composio.dev/toolkits/epic_games) - Epic Games is a leading video game publisher and digital storefront, known for Fortnite and Unreal Engine. It lets gamers access, manage, and purchase games all in one place. - [Fal.ai](https://composio.dev/toolkits/fal_ai) - Fal.ai is a generative media platform offering 600+ AI models for images, video, voice, and audio. Developers use Fal.ai for fast, scalable access to cutting-edge generative AI tools. - [Giphy](https://composio.dev/toolkits/giphy) - Giphy is the largest online library for searching and sharing GIFs and stickers. Instantly add vibrant animated content to your apps, chats, and workflows. - [Headout](https://composio.dev/toolkits/headout) - Headout is a global platform for booking travel experiences, tours, and entertainment. It helps users discover and secure activities at top destinations, all in one place. - [Listennotes](https://composio.dev/toolkits/listennotes) - Listennotes is a powerful podcast search engine with a massive global database. Discover, search, and curate podcasts from around the world in seconds. - [News api](https://composio.dev/toolkits/news_api) - News api is a REST API for searching and retrieving live news articles from across the web. Instantly access headlines, coverage, and breaking stories from thousands of sources. - [RAWG Video Games Database](https://composio.dev/toolkits/rawg_video_games_database) - RAWG Video Games Database is the largest video game discovery and info service. Instantly access comprehensive details, ratings, and release dates for thousands of games. - [Seat geek](https://composio.dev/toolkits/seat_geek) - SeatGeek is a live event platform offering APIs for concerts, sports, and theater data. Instantly access events, venues, and performers info for smarter ticketing and discovery. - [Shotstack](https://composio.dev/toolkits/shotstack) - Shotstack is a cloud platform for programmatically generating videos, images, and audio. Automate creative content production at scale with flexible RESTful APIs. - [Spotify](https://composio.dev/toolkits/spotify) - Spotify is a streaming service for music and podcasts with millions of tracks from artists worldwide. Enjoy personalized playlists, recommendations, and seamless listening across all your devices. - [Ticketmaster](https://composio.dev/toolkits/ticketmaster) - Ticketmaster is a global platform for event discovery, ticket sales, and live entertainment management. Get real-time access to events and streamline ticketing for fans and organizers. - [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. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Imagekit io MCP? With a standalone Imagekit io MCP server, the agents and LLMs can only access a fixed set of Imagekit io tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Imagekit io 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 Imagekit io tools. ### Can I manage the permissions and scopes for Imagekit io while using Tool Router? Yes, absolutely. You can configure which Imagekit io 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 Imagekit io data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)