# How to integrate Fal.ai MCP with Mastra AI

```json
{
  "title": "How to integrate Fal.ai MCP with Mastra AI",
  "toolkit": "Fal.ai",
  "toolkit_slug": "fal_ai",
  "framework": "Mastra AI",
  "framework_slug": "mastra-ai",
  "url": "https://composio.dev/toolkits/fal_ai/framework/mastra-ai",
  "markdown_url": "https://composio.dev/toolkits/fal_ai/framework/mastra-ai.md",
  "updated_at": "2026-03-29T06:33:16.683Z"
}
```

## Introduction

This guide walks you through connecting Fal.ai to Mastra AI using the Composio tool router. By the end, you'll have a working Fal.ai agent that can generate a photorealistic portrait of a cat, create a 15-second ai-generated promo video, synthesize an audio clip saying 'welcome home!' through natural language commands.
This guide will help you understand how to give your Mastra AI agent real control over a Fal.ai account through Composio's Fal.ai MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Fal.ai with

- [ChatGPT](https://composio.dev/toolkits/fal_ai/framework/chatgpt)
- [Antigravity](https://composio.dev/toolkits/fal_ai/framework/antigravity)
- [OpenAI Agents SDK](https://composio.dev/toolkits/fal_ai/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/fal_ai/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/fal_ai/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/fal_ai/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/fal_ai/framework/codex)
- [Cursor](https://composio.dev/toolkits/fal_ai/framework/cursor)
- [VS Code](https://composio.dev/toolkits/fal_ai/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/fal_ai/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/fal_ai/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/fal_ai/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/fal_ai/framework/cli)
- [Google ADK](https://composio.dev/toolkits/fal_ai/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/fal_ai/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/fal_ai/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/fal_ai/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/fal_ai/framework/crew-ai)

## 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 Fal.ai tools
- Connect Mastra's MCP client to the Composio generated MCP URL
- Fetch Fal.ai 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 Fal.ai 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 Fal.ai MCP server, and what's possible with it?

The Fal.ai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fal.ai account. It provides structured and secure access so your agent can perform Fal.ai operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `FAL_AI_CANCEL_QUEUE_REQUEST` | Cancel Queue Request | Tool to cancel a queued or in-progress request in fal.ai's queue system. Use when you need to stop a request before it completes. Note that cancellation only succeeds if the request hasn't started processing; if already completed, returns an error status. Even with successful cancellation, the request may still execute if it was near the front of the queue. |
| `FAL_AI_ESTIMATE_PRICING` | Estimate Pricing | Tool to estimate pricing for fal.ai model endpoints. Use when you need to calculate expected costs for API calls or unit-based usage across one or more endpoints. |
| `FAL_AI_GET_JWKS` | Get JWKS for Webhook Verification | Tool to retrieve public keys for webhook signature verification. Returns a JSON Web Key Set containing ED25519 public keys. Use when you need to verify webhook signatures from fal.ai. The keys are cacheable but should be refreshed at least every 24 hours. |
| `FAL_AI_GET_MODELS` | Get Models | Tool to discover and search fal.ai model endpoints. Use when you need to list all models, find specific models by ID, or search by category/query. Supports pagination and optional expansion of OpenAPI schemas. |
| `FAL_AI_GET_MODEL_PRICING` | Get Model Pricing | Tool to retrieve unit pricing for model endpoints. Returns pricing information including unit price, billing unit, and currency. Use when you need to check costs for specific fal.ai models. |
| `FAL_AI_GET_QUEUE_REQUEST_RESULT` | Get Queue Request Result | Tool to retrieve the final result of a completed queue request. Use when you need to get the output of a model request that was submitted to the queue and has finished processing. Only works after request status transitions to COMPLETED. |
| `FAL_AI_GET_QUEUE_REQUEST_STATUS_WITH_LOGS` | Get Queue Request Status With Logs | Tool to retrieve the current status of a queued request with detailed logging information. Use when you need to monitor a queued request's progress and access execution logs for debugging or tracking purposes. Logs include timestamps, severity levels, and detailed messages about request processing. |
| `FAL_AI_CHECK_QUEUE_REQUEST_STATUS` | Check Queue Request Status | Tool to check the status of a queued request in fal.ai. Use when you need to monitor the progress of an async request. Returns different information based on status: queue position when IN_QUEUE, logs when IN_PROGRESS or COMPLETED. |
| `FAL_AI_STREAM_REQUEST_STATUS_UPDATES` | Stream Request Status Updates | Tool to stream request status updates via SSE. Use when you need real-time updates on a queued request's processing state. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Fal.ai MCP server is an implementation of the Model Context Protocol that connects your AI agent to Fal.ai. It provides structured and secure access so your agent can perform Fal.ai operations on your behalf through a secure, permission-based interface.
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:
- Node.js 18 or higher
- A Composio account with an active API key
- An OpenAI API key
- Basic familiarity with TypeScript

### 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 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.
- This key lets your Mastra agent talk to Composio and reach Fal.ai through MCP.

### 2. Install dependencies

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

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import libraries and validate environment

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
```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,
});
```

### 5. Create a Tool Router session for Fal.ai

What's happening:
- create spins up a short-lived MCP HTTP endpoint for this user
- The toolkits array contains "fal_ai" for Fal.ai access
- session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
```typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["fal_ai"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Fal.ai MCP URL:", composioMCPUrl);
```

### 6. Configure Mastra MCP client and fetch tools

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 Fal.ai toolkit
```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);
```

### 7. Create the Mastra agent

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

### 8. Set up interactive chat interface

What's happening:
- messages keeps the full conversation history in Mastra's expected format
- agent.generate runs the agent with conversation history and Fal.ai 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
```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: {
        fal_ai: 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);
});
```

## Complete Code

```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: ["fal_ai"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "fal_ai-mastra-agent",
    instructions: "You are an AI agent with Fal.ai 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: { fal_ai: 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 Fal.ai 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

## How to build Fal.ai MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/fal_ai/framework/chatgpt)
- [Antigravity](https://composio.dev/toolkits/fal_ai/framework/antigravity)
- [OpenAI Agents SDK](https://composio.dev/toolkits/fal_ai/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/fal_ai/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/fal_ai/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/fal_ai/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/fal_ai/framework/codex)
- [Cursor](https://composio.dev/toolkits/fal_ai/framework/cursor)
- [VS Code](https://composio.dev/toolkits/fal_ai/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/fal_ai/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/fal_ai/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/fal_ai/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/fal_ai/framework/cli)
- [Google ADK](https://composio.dev/toolkits/fal_ai/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/fal_ai/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/fal_ai/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/fal_ai/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/fal_ai/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.
- [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.
- [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.
- [Figma](https://composio.dev/toolkits/figma) - Figma is a collaborative interface design tool for teams and individuals. It streamlines design workflows with real-time collaboration and easy sharing.
- [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.
- [Abyssale](https://composio.dev/toolkits/abyssale) - Abyssale is a creative automation platform for generating images, videos, GIFs, PDFs, and HTML5 content programmatically. It streamlines and scales visual content production for marketing, design, and operations teams.
- [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.
- [Alttext ai](https://composio.dev/toolkits/alttext_ai) - AltText.ai is a service that generates alt text for images automatically. It helps boost accessibility and SEO for your visual content.
- [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.
- [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.
- [Bannerbear](https://composio.dev/toolkits/bannerbear) - Bannerbear is an API-driven platform for generating images and videos automatically at scale. It helps businesses create custom graphics, social visuals, and marketing assets using powerful templates.
- [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.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Fal.ai MCP?

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

### Can I use Tool Router MCP with Mastra AI?

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 Fal.ai tools.

### Can I manage the permissions and scopes for Fal.ai while using Tool Router?

Yes, absolutely. You can configure which Fal.ai 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 Fal.ai data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)