# How to integrate Modelry MCP with Claude Code ```json { "title": "How to integrate Modelry MCP with Claude Code", "toolkit": "Modelry", "toolkit_slug": "modelry", "framework": "Claude Code", "framework_slug": "claude-code", "url": "https://composio.dev/toolkits/modelry/framework/claude-code", "markdown_url": "https://composio.dev/toolkits/modelry/framework/claude-code.md", "updated_at": "2026-05-12T10:19:19.161Z" } ``` ## Introduction Manage your Modelry directly from Claude Code with zero worries about OAuth hassles, API-breaking issues, or reliability and security concerns. You can do this in two different ways: - Via [Composio Connect](https://dashboard.composio.dev/login?utm_source=toolkits&utm_medium=framework_template&utm_campaign=claude-code&utm_content=composio_connect&next=%2F~%2Forg%2Fconnect%2Fclients%2Fclaude-code) - Direct and easiest approach - Via [Composio SDK](https://docs.composio.dev/docs?utm_source=toolkits&utm_medium=framework_template&utm_campaign=claude-code&utm_content=composio_sdk) - Programmatic approach with more control ## Also integrate Modelry with - [OpenAI Agents SDK](https://composio.dev/toolkits/modelry/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/modelry/framework/claude-agents-sdk) - [Claude Cowork](https://composio.dev/toolkits/modelry/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/modelry/framework/codex) - [OpenClaw](https://composio.dev/toolkits/modelry/framework/openclaw) - [Hermes](https://composio.dev/toolkits/modelry/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/modelry/framework/cli) - [Google ADK](https://composio.dev/toolkits/modelry/framework/google-adk) - [LangChain](https://composio.dev/toolkits/modelry/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/modelry/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/modelry/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/modelry/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/modelry/framework/crew-ai) ## TL;DR - Only one MCP URL to connect multiple apps with Claude Code with zero auth hassles. - Programmatic tool calling allows LLMs to write its code in a remote workbench to handle complex tool chaining. Reduces to-and-fro with LLMs for frequent tool calling. - Handling Large tool responses out of LLM context to minimize context rot. - Dynamic just-in-time access to 20,000 tools across 1000+ other Apps for cross-app workflows. It loads the tools you need, so LLMs aren't overwhelmed by tools you don't need. ## Connect Modelry to Claude Code ### Connecting Modelry to Claude Code using Composio 1. Add the Composio MCP to Claude ```bash claude mcp add --scope user --transport http composio https://connect.composio.dev/mcp ``` ## What is Claude Code? Claude Code is Anthropic's command line developer tool that lets you use Claude directly inside your terminal. Instead of switching between your editor, browser, and chat, you can stay in your project folder and ask Claude to help you build, debug, refactor, and understand code right where you're working. Key features include: - Terminal-Native Experience: Work with Claude directly in your command line without switching contexts - MCP Support: Built-in support for Model Context Protocol servers to extend Claude's capabilities - Project Context: Claude understands your project structure and can read, write, and modify files - Interactive Development: Ask questions, debug code, and get help in real-time while coding - Multi-Platform: Works on macOS, Linux, WSL, and Windows ## What is the Modelry MCP server, and what's possible with it? The Modelry MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Modelry account. It provides structured and secure access to your machine learning model management, so your agent can perform actions like listing modeling requests, creating workspaces, retrieving embed details, and managing products on your behalf. - Workspace management: Easily create new workspaces or fetch details about existing ones to keep your projects organized and separated. - Embed and product operations: List all available embeds, get detailed information, or delete embeds and products as needed for smooth deployment and maintenance. - Repository handling: Retrieve details of product repositories or remove repositories you no longer need—all with structured agent commands. - Modeling request tracking: Quickly list all 3D modeling requests tied to your account to monitor progress and manage workflows efficiently. - Secure automated actions: Let your agent handle repetitive or administrative model management tasks securely, saving you time and effort. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `MODELRY_CREATE_WORKSPACE` | Create Workspace | Create a new workspace or return an existing one with the same name. Workspaces are used to organize products and embeds in Modelry. If workspace creation is not supported by the API, this tool will return an existing workspace matching the requested name. | | `MODELRY_DELETE_EMBED` | Delete Modelry Embed | Tool to delete an embed. Tries multiple common endpoint patterns and treats 404 as idempotent success after exhausting candidates (embed already deleted or not found). | | `MODELRY_DELETE_PRODUCT` | Delete Modelry Product | Permanently deletes a product from Modelry by its ID. Use this action to remove a product that is no longer needed. This operation is idempotent - deleting an already-deleted product will succeed without error. Prerequisites: - Obtain the product ID using MODELRY_LIST_PRODUCTS first - Ensure you have delete permissions for the product WARNING: This action is destructive and cannot be undone. | | `MODELRY_DELETE_PRODUCT_REPOSITORY` | Delete Product Repository | Permanently delete a product repository from Modelry. This action is idempotent - deleting a non-existent repository returns success. Use the list product repositories action first to get valid repository IDs. | | `MODELRY_DELETE_WORKSPACE` | Delete Modelry Workspace | Permanently deletes a Modelry workspace. This action is idempotent - deleting a non-existent workspace will return success. Use the list workspaces action first to get valid workspace IDs. WARNING: This is a destructive action that cannot be undone. | | `MODELRY_GET_EMBED` | Get Embed | Retrieve details of a specific Modelry embed (3D viewer or AR experience for eCommerce). Use MODELRY_LIST_EMBEDS first to obtain valid embed IDs. Returns embed metadata including status, workspace, and configuration details. | | `MODELRY_GET_WORKSPACE` | Get Workspace | Retrieves details for a specific Modelry workspace by its ID or name. The workspace ID can be obtained from the List Workspaces action. This action fetches all workspaces and returns the matching one. | | `MODELRY_LIST_EMBEDS` | List Embeds | List embeds in Modelry. Embeds are 3D viewer/AR embed codes for products. Use to retrieve embed IDs for downstream actions (e.g., MODELRY_GET_EMBED, MODELRY_DELETE_EMBED). Returns empty list if no embeds exist. Supports pagination and optional workspace filtering. | | `MODELRY_LIST_MODELING_REQUESTS` | List Modeling Requests | List all 3D modeling requests in a workspace. Requires workspace_id to scope the request. Returns modeling requests with their status and metadata. | | `MODELRY_LIST_PRODUCT_REPOSITORIES` | List Product Repositories | Tool to list all product repositories in a workspace. Use after confirming the workspace ID. | | `MODELRY_LIST_PRODUCTS` | List Modelry Products | List all products in Modelry. Returns paginated product data including IDs, names, and metadata. Use this to retrieve product IDs needed for other product-related actions like delete or get details. Optionally scope to a specific workspace using workspace_id parameter. | | `MODELRY_LIST_WORKSPACES` | List Modelry Workspaces | Tool to list all workspaces in Modelry. Use when you need to retrieve available workspaces after authenticating. | | `MODELRY_ORDER_MODELING_SERVICE` | Order Modeling Service | Tool to place an order for 3D modeling services. Use when workspace and product IDs are known and modeling specifications are ready. | | `MODELRY_TRACK_MODELING_PROGRESS` | Track Modeling Progress | Tool to track the progress of a 3D modeling request. Use after initiating a modeling job to poll current status and completion percentage. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Modelry MCP server is an implementation of the Model Context Protocol that connects Claude Code (and other AI assistants like Claude and Cursor) directly to your Modelry account. It provides structured and secure access so Claude can perform Modelry operations on your behalf. 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: - Claude Pro, Max, or API billing enabled Anthropic account - Composio API Key - A Modelry account - Basic knowledge of Python or TypeScript ### 1. Install Claude Code To install Claude Code, use one of the following methods based on your operating system: ```bash # macOS, Linux, WSL curl -fsSL https://claude.ai/install.sh | bash # Windows PowerShell irm https://claude.ai/install.ps1 | iex # Windows CMD curl -fsSL https://claude.ai/install.cmd -o install.cmd && install.cmd && del install.cmd ``` ### 2. Set up Claude Code Open a terminal, go to your project folder, and start Claude Code: - Claude Code will open in your terminal - Follow the prompts to sign in with your Anthropic account - Complete the authentication flow - Once authenticated, you can start using Claude Code ```bash cd your-project-folder claude ``` ### 3. Set up environment variables Create a .env file in your project root with the following variables: - COMPOSIO_API_KEY authenticates with Composio (get it from [Composio dashboard](https://dashboard.composio.dev/login?utm_source=toolkits&utm_medium=framework_template&utm_campaign=claude-code&utm_content=api_key&next=%2F~%2Forg%2Fconnect%2Fclients%2Fclaude-code)) - USER_ID identifies the user for session management (use any unique identifier) ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here ``` ### 4. Install Composio library No description provided. ```python pip install composio-core python-dotenv ``` ```typescript npm install @composio/core dotenv ``` ### 5. Generate Composio MCP URL No description provided. ```python import os from composio import Composio from dotenv import load_dotenv load_dotenv() COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") USER_ID = os.getenv("USER_ID") composio_client = Composio(api_key=COMPOSIO_API_KEY) composio_session = composio_client.create( user_id=USER_ID, toolkits=["modelry"], ) COMPOSIO_MCP_URL = composio_session.mcp.url print(f"MCP URL: {COMPOSIO_MCP_URL}") print(f"\nUse this command to add to Claude Code:") print(f'claude mcp add --transport http modelry-composio "{COMPOSIO_MCP_URL}" --headers "X-API-Key:{COMPOSIO_API_KEY}"') ``` ```typescript import 'dotenv/config'; import { Composio } from '@composio/core'; const { COMPOSIO_API_KEY, USER_ID } = process.env; if (!COMPOSIO_API_KEY || !USER_ID) { throw new Error('COMPOSIO_API_KEY and USER_ID required in .env'); } const composioClient = new Composio({ apiKey: COMPOSIO_API_KEY }); const composioSession = await composioClient.create(USER_ID, { toolkits: ['modelry'], }); const composioMcpUrl = composioSession?.mcp.url; console.log(`MCP URL: ${composioMcpUrl}`); console.log(`\nUse this command to add to Claude Code:`); console.log(`claude mcp add --transport http modelry-composio "${composioMcpUrl}" --headers "X-API-Key:${COMPOSIO_API_KEY}"`); ``` ### 6. Run the script and copy the MCP URL No description provided. ```python python generate_mcp_url.py ``` ```typescript node --loader ts-node/esm generate_mcp_url.ts # or if using tsx tsx generate_mcp_url.ts ``` ### 7. Add Modelry MCP to Claude Code In your terminal, add the MCP server using the command from the previous step. The command format is: - claude mcp add registers a new MCP server with Claude Code - --transport http specifies that this is an HTTP-based MCP server - The server name (modelry-composio) is how you'll reference it - The URL points to your Composio Tool Router session - --headers includes your Composio API key for authentication After running the command, close the current Claude Code session and start a new one for the changes to take effect. ```bash claude mcp add --transport http modelry-composio "YOUR_MCP_URL_HERE" --headers "X-API-Key:YOUR_COMPOSIO_API_KEY" # Then restart Claude Code exit claude ``` ### 8. Verify the installation Check that your Modelry MCP server is properly configured. - This command lists all MCP servers registered with Claude Code - You should see your modelry-composio entry in the list - This confirms that Claude Code can now access Modelry tools If everything is wired up, you should see your modelry-composio entry listed: ```bash claude mcp list ``` ### 9. Authenticate Modelry The first time you try to use Modelry tools, you'll be prompted to authenticate. - Claude Code will detect that you need to authenticate with Modelry - It will show you an authentication link - Open the link in your browser (or copy/paste it) - Complete the Modelry authorization flow - Return to the terminal and start using Modelry through Claude Code Once authenticated, you can ask Claude Code to perform Modelry operations in natural language. For example: - "List all modeling requests in my workspace" - "Create a new workspace for my models" - "Get details for a specific embed" ## Complete Code ```python import os from composio import Composio from dotenv import load_dotenv load_dotenv() COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") USER_ID = os.getenv("USER_ID") composio_client = Composio(api_key=COMPOSIO_API_KEY) composio_session = composio_client.create( user_id=USER_ID, toolkits=["modelry"], ) COMPOSIO_MCP_URL = composio_session.mcp.url print(f"MCP URL: {COMPOSIO_MCP_URL}") print(f"\nUse this command to add to Claude Code:") print(f'claude mcp add --transport http modelry-composio "{COMPOSIO_MCP_URL}" --headers "X-API-Key:{COMPOSIO_API_KEY}"') ``` ```typescript import 'dotenv/config'; import { Composio } from '@composio/core'; const { COMPOSIO_API_KEY, USER_ID } = process.env; if (!COMPOSIO_API_KEY || !USER_ID) { throw new Error('COMPOSIO_API_KEY and USER_ID required in .env'); } const composioClient = new Composio({ apiKey: COMPOSIO_API_KEY }); const composioSession = await composioClient.create(USER_ID, { toolkits: ['modelry'], }); const composioMcpUrl = composioSession?.mcp.url; console.log(`MCP URL: ${composioMcpUrl}`); console.log(`\nUse this command to add to Claude Code:`); console.log(`claude mcp add --transport http modelry-composio "${composioMcpUrl}" --headers "X-API-Key:${COMPOSIO_API_KEY}"`); ``` ## Conclusion You've successfully integrated Modelry with Claude Code using Composio's MCP server. Now you can interact with Modelry directly from your terminal using natural language commands. Key features of this setup: - Terminal-native experience without switching contexts - Natural language commands for Modelry operations - Secure authentication through Composio's managed MCP - Tool Router for dynamic tool discovery and execution Next steps: - Try asking Claude Code to perform various Modelry operations - Add more toolkits to your Tool Router session for multi-app workflows - Integrate this setup into your development workflow for increased productivity You can extend this by adding more toolkits, implementing custom workflows, or building automation scripts that leverage Claude Code's capabilities. ## How to build Modelry MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/modelry/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/modelry/framework/claude-agents-sdk) - [Claude Cowork](https://composio.dev/toolkits/modelry/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/modelry/framework/codex) - [OpenClaw](https://composio.dev/toolkits/modelry/framework/openclaw) - [Hermes](https://composio.dev/toolkits/modelry/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/modelry/framework/cli) - [Google ADK](https://composio.dev/toolkits/modelry/framework/google-adk) - [LangChain](https://composio.dev/toolkits/modelry/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/modelry/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/modelry/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/modelry/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/modelry/framework/crew-ai) ## Related Toolkits - [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. - [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service. - [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows. - [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow. - [Ai ml api](https://composio.dev/toolkits/ai_ml_api) - Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows. - [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application. - [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities. - [Anthropic administrator](https://composio.dev/toolkits/anthropic_administrator) - Anthropic administrator is an API for managing Anthropic organizational resources like members, workspaces, and API keys. It helps you automate admin tasks and streamline resource management across your Anthropic organization. - [Api labz](https://composio.dev/toolkits/api_labz) - Api labz is a platform offering a suite of AI-driven APIs and workflow tools. It helps developers automate tasks and build smarter, more efficient applications. - [Apipie ai](https://composio.dev/toolkits/apipie_ai) - Apipie ai is an AI model aggregator offering a single API for accessing top AI models from multiple providers. It helps developers build cost-efficient, latency-optimized AI solutions without juggling multiple integrations. - [Astica ai](https://composio.dev/toolkits/astica_ai) - Astica ai provides APIs for computer vision, NLP, and voice synthesis. Integrate advanced AI features into your app with a single API key. - [Bigml](https://composio.dev/toolkits/bigml) - BigML is a machine learning platform that lets you build, train, and deploy predictive models from your data. Its intuitive interface and robust API make machine learning accessible and efficient. - [Botbaba](https://composio.dev/toolkits/botbaba) - Botbaba is a platform for building, managing, and deploying conversational AI chatbots across messaging channels. It streamlines chatbot automation, making it easier to integrate AI into customer interactions. - [Botpress](https://composio.dev/toolkits/botpress) - Botpress is an open-source platform for building, deploying, and managing chatbots. It helps teams automate conversations and deliver rich, interactive messaging experiences. - [Chatbotkit](https://composio.dev/toolkits/chatbotkit) - Chatbotkit is a platform for building and managing AI-powered chatbots using robust APIs and SDKs. It lets you easily add conversational AI to your apps for better user engagement. - [Cody](https://composio.dev/toolkits/cody) - Cody is an AI assistant built for businesses, trained on your company's knowledge and data. It delivers instant answers and insights, tailored for your team. - [Context7 MCP](https://composio.dev/toolkits/context7_mcp) - Context7 MCP delivers live, version-specific code docs and examples right from the source. It helps developers and AI agents instantly retrieve authoritative programming info—no more out-of-date docs. - [Customgpt](https://composio.dev/toolkits/customgpt) - CustomGPT.ai lets you build and deploy chatbots tailored to your own data and business needs. Get precise and context-aware AI conversations without writing code. - [Datarobot](https://composio.dev/toolkits/datarobot) - Datarobot is a machine learning platform that automates model development, deployment, and monitoring. It empowers organizations to quickly gain predictive insights from large datasets. - [Deepgram](https://composio.dev/toolkits/deepgram) - Deepgram is an AI-powered speech recognition platform for accurate audio transcription and understanding. It enables fast, scalable speech-to-text with advanced audio intelligence features. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Modelry MCP? With a standalone Modelry MCP server, the agents and LLMs can only access a fixed set of Modelry tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Modelry and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Claude Code? Yes, you can. Claude Code 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 Modelry tools. ### Can I manage the permissions and scopes for Modelry while using Tool Router? Yes, absolutely. You can configure which Modelry 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 Modelry data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)