Modelry MCP for AI Agents

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Modelry MCP or direct API to deploy models, monitor training runs, manage datasets, and retrieve real-time performance metrics through natural language.

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Modelry is a platform for building, deploying, and managing machine learning models. It streamlines the end-to-end ML lifecycle so teams can ship models faster and more reliably.

14 Tools

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TOOL ROUTER PLAYGROUND
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TOOLS

Supported Tools

Every Modelry action and event your agent gets out of the box.

Create Workspace

Create a new workspace or return an existing one with the same name.

Delete Modelry Embed

Tool to delete an embed.

Delete Modelry Product

Permanently deletes a product from Modelry by its ID.

Delete Product Repository

Permanently delete a product repository from Modelry.

Delete Modelry Workspace

Permanently deletes a Modelry workspace.

Get Embed

Retrieve details of a specific Modelry embed (3D viewer or AR experience for eCommerce).

Get Workspace

Retrieves details for a specific Modelry workspace by its ID or name.

List Embeds

List embeds in Modelry.

List Modeling Requests

List all 3D modeling requests in a workspace.

List Product Repositories

Tool to list all product repositories in a workspace.

List Modelry Products

List all products in Modelry.

List Modelry Workspaces

Tool to list all workspaces in Modelry.

Order Modeling Service

Tool to place an order for 3D modeling services.

Track Modeling Progress

Tool to track the progress of a 3D modeling request.

SETUP GUIDE

Connect Modelry MCP Tool with your Agent

1

Install Composio

typescript
npm install @composio/core ai @ai-sdk/mcp @ai-sdk/openai
Install the Composio SDK and your agent framework
2

Create a session with MCP enabled

typescript
import { Composio } from "@composio/core";

const composio = new Composio();
const { mcp } = await composio.create("your-user-id", {
  toolkits: ["modelry"],
  mcp: true,
});
Create a session scoped to Modelry and read its MCP URL and headers
3

Connect your agent to the MCP server

typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { openai } from "@ai-sdk/openai";
import { generateText, stepCountIs } from "ai";

const client = await createMCPClient({
  transport: { type: "http", url: mcp.url, headers: mcp.headers },
});

const { text } = await generateText({
  model: openai("gpt-5.6-sol"),
  tools: await client.tools(),
  prompt: "List all 3D modeling requests in my workspace",
  stopWhen: stepCountIs(10),
});

console.log(text);
await client.close();
Pass the session's MCP URL and headers to your agent and run a Modelry request
SETUP GUIDE

Connect Modelry API Tool with your Agent

1

Install Composio

typescript
npm install @composio/core @composio/openai openai
Install the Composio SDK, the OpenAI provider, and the OpenAI SDK
2

Create a Composio session

typescript
import OpenAI from "openai";
import { Composio } from "@composio/core";
import { OpenAIResponsesProvider } from "@composio/openai";

const composio = new Composio({ provider: new OpenAIResponsesProvider() });
const client = new OpenAI();

const session = await composio.create("your-user-id", { toolkits: ["modelry"] });
const tools = await session.tools();
Initialize Composio with the OpenAI Responses provider and create a session scoped to Modelry
3

Run Modelry tools with your agent

typescript
let response = await client.responses.create({
  model: "gpt-5.6-sol",
  tools,
  input: [{ role: "user", content: "List all 3D modeling requests in my workspace" }],
});

while (response.output.some((o) => o.type === "function_call")) {
  const outputs = await composio.provider.handleToolCalls(session, response.output);
  response = await client.responses.create({
    model: "gpt-5.6-sol",
    tools,
    previous_response_id: response.id,
    input: outputs,
  });
}

console.log(response.output_text);
Send a request, execute the Modelry tool calls through the session, and print the final answer

Why Use Composio?

AI Native Modelry Integration

  • Supports both Modelry MCP and direct API based integrations
  • Structured, LLM-friendly schemas for reliable tool execution
  • Rich coverage for launching, monitoring, and managing your ML models

Managed Auth

  • Built-in API key handling with secure storage and auto-rotation
  • Central place to manage and revoke Modelry credentials
  • Per user and per environment credentials instead of hard-coded keys

Agent Optimized Design

  • Tools are tuned using real error and success rates to improve reliability over time
  • Comprehensive execution logs so you always know what ran, when, and on whose behalf

Enterprise Grade Security

  • Fine-grained RBAC so you control which agents and users can access Modelry
  • Scoped, least privilege access to Modelry resources
  • Full audit trail of agent actions to support review and compliance
FAQ

Frequently asked questions

Yes, Modelry requires you to configure your own API key credentials. Once set up, Composio handles secure credential storage and API request handling for you.

Yes! Composio's Tool Router enables agents to use multiple toolkits. Learn more.

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. Learn more.

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

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