How to integrate Runway MCP with Mastra AI

This guide walks you through connecting Runway to Mastra AI using the Composio tool router. By the end, you'll have a working Runway agent that can generate images, create videos, produce speech, make sound effects, and manage documents through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Runway account through Composio's Runway MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Runway logoRunway
Api Key

Runway is a generative AI media platform for creating and transforming video, images, audio, avatars, voices, and creative workflows. It helps teams build high-quality visual content faster with API-driven media generation.

22 Tools

Introduction

This guide walks you through connecting Runway to Mastra AI using the Composio tool router. By the end, you'll have a working Runway agent that can generate images, create videos, produce speech, make sound effects, and manage documents through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Runway account through Composio's Runway MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Runway with

TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Runway tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Runway tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Runway agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

What is the Runway MCP server, and what's possible with it?

The Runway MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Runway account. It provides structured and secure access to your generative media, workflows, knowledge documents, and account usage, so your agent can generate media, transform content, run workflows, manage documents, and monitor activity on your behalf.

  • Image and video generation: Have your agent create images from prompts, generate videos from text, or animate existing images with your chosen Runway model.
  • Media transformation and upscaling: Direct your agent to restyle existing videos or upscale images and videos for higher-quality results.
  • Speech and sound creation: Let the agent synthesize speech with supported voices or generate sound effects from written descriptions.
  • Workflow and knowledge management: Instruct your agent to inspect and run published workflows, then create, review, update, or delete knowledge documents used by avatar workflows.
  • Task, credit, and usage monitoring: Have your agent check generation progress, retrieve completed media, cancel running tasks, and review credit balances, quotas, and daily usage.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Runway through MCP.
3

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models
5

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session
6

Create a Tool Router session for Runway

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["runway"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Runway MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "runway" for Runway access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Runway toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "runway-mastra-agent",
    instructions: "You are an AI agent with Runway tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM
9

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        runway: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Runway toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Runway and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["runway"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      runway: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "runway-mastra-agent",
    instructions: "You are an AI agent with Runway tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { runway: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Runway through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows
TOOLS

Supported Tools

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

Cancel Task

Cancel a running Runway task or delete its task record.

Create Document

Create a Runway knowledge document from markdown or plain text for reuse by avatar workflows.

Create Ephemeral Upload

Create only a temporary Runway media upload slot and return its presigned multipart form details and runway:// URI.

Delete Document

Permanently delete a Runway knowledge document by its ID.

Generate Image

Start a Runway text-to-image or reference-guided image generation task and return its task ID and estimated credit cost.

Generate Sound Effect

Generate an audio effect from a text prompt and return the task ID and estimated credit cost.

Generate Speech

Synthesize speech with Runway using an exact model-specific voice and option contract, then return the task ID and estimated credit cost.

Generate Video from Image

Animate one or more input images with a selected Runway model and return the task ID and estimated credit cost.

Generate Video from Text

Start a Runway text-to-video task with a model-specific typed request and return its task ID and estimated credit cost.

Get Document

Get one Runway knowledge document, including its full content and the avatars that currently use it.

Get Organization

Return the connected Runway organization's credit balance, monthly credit spend cap, exact per-model quotas, and current daily generation usage.

Get Task

Get the current status, cost, output URLs, and failure details for a Runway generation task.

Get Usage

Return daily Runway credit usage by model for an optional UTC date range of up to 90 days.

Get Workflow

Get a published Runway workflow version and its graph so node IDs and output keys can be inspected before running the workflow.

Get Workflow Invocation

Get the current status, completed node output URLs, and node or invocation failure details for a Runway workflow invocation.

List Documents

List Runway knowledge documents one page at a time, with sorting and an opaque continuation cursor.

List Workflows

List the connected account's published Runway workflows and their available versions, ordered as returned by Runway.

Run Workflow

Invoke a published Runway workflow, optionally overriding graph node outputs, and return the created workflow invocation ID.

Transform Video

Transform or restyle an existing video with Runway and return the created task ID and estimated credit cost.

Update Document

Change the name, content, or both for an existing Runway knowledge document.

Upscale Image

Start a Runway image upscaling task and return its task ID and estimated credit cost.

Upscale Video

Start a Runway video upscaling task and return its task ID and estimated credit cost.

FAQ

Frequently asked questions

With a standalone Runway MCP server, the agents and LLMs can only access a fixed set of Runway tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Runway and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Mastra 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 Runway tools.

Yes, absolutely. You can configure which Runway 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.

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 Runway data and credentials are handled as safely as possible.

Start with Runway.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Runway tool your agent needs.Free to start.

Start building