How to integrate Uploadcare MCP with LangChain

This guide walks you through connecting Uploadcare to LangChain using the Composio tool router. By the end, you'll have a working Uploadcare agent that can list all uploaded files from last week, rotate image file by 90 degrees clockwise, get direct download link for specific file through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Uploadcare account through Composio's Uploadcare MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Uploadcare

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Uploadcare is a file handling platform for uploading, storing, and delivering files at scale. It streamlines file management, processing, and delivery for web and mobile apps.

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Introduction

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

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

Also integrate Uploadcare with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK Vercel AI SDK Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

Get and set up your OpenAI and Composio API keys
Connect your Uploadcare project to Composio
Create a Tool Router MCP session for Uploadcare
Initialize an MCP client and retrieve Uploadcare tools
Build a LangChain agent that can interact with Uploadcare
Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

Agent Framework: Build agents that can use tools and make decisions
MCP Integration: Connect to external services through Model Context Protocol adapters
Memory Management: Maintain conversation history across interactions
Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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

The Uploadcare MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Uploadcare account. It provides structured and secure access to your file storage, processing, and delivery pipeline, so your agent can perform actions like listing files, retrieving file info, managing webhooks, rotating images, and handling file metadata on your behalf.

Comprehensive file listing and retrieval: Ask your agent to list all files stored in your Uploadcare project, filter by criteria, or fetch detailed metadata for any file.
Direct file download and sharing: Effortlessly generate secure, temporary download links for your files so you can share them or integrate with other services.
Automated image processing: Let your agent rotate images by 90, 180, or 270 degrees, making quick edits or transformations without manual intervention.
Webhook management for event automation: Easily create, list, or delete webhooks so your agent can subscribe to file events and enable real-time notifications or integrations.
Metadata and group management: Enable your agent to update or delete file metadata and organize files into groups for streamlined file handling and workflows.

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:

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

Step-by-step Guide

Step by step10 STEPS

Prerequisites

Before starting this tutorial, make sure you have:

Python 3.10 or higher installed on your system
A Composio account with an API key
An OpenAI API key
Basic familiarity with Python and async programming

Getting API Keys for OpenAI and Composio

OpenAI API Key

Go to the OpenAI dashboard 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.
Navigate to your API settings and generate a new API key.
Store this key securely as you'll need it for authentication.

Install dependencies

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

@composio/langchain provides Composio integration for LangChain
@langchain/mcp-adapters enables MCP client connections
@langchain/core is the core agent framework
dotenv/config loads environment variables

Set up environment variables

bash

COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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's API
COMPOSIO_USER_ID identifies the user for session management
OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();

What's happening:

We're importing LangChain's MCP adapter and Composio SDK
The dotenv/config import loads environment variables from your .env file
This setup prepares the foundation for connecting LangChain with Uploadcare functionality through MCP

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

What's happening:

We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
Creating a Composio instance that will manage our connection to Uploadcare tools
Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['uploadcare']
    }
);

const url = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Uploadcare tools
The create method takes the user ID and specifies which toolkits should be available
The returned session.mcp.url is the MCP server URL that your agent will use
This approach allows the agent to dynamically load and use Uploadcare tools as needed

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "uploadcare-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });

What's happening:

We're creating a MultiServerMCPClient that connects to our Uploadcare MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available Uploadcare tools that the agent can use
We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Uploadcare related question or task to the agent.\n");

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

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;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });

What's happening:

We initialize an empty conversationHistory list to maintain context across interactions
A readline interface is used to continuously accept user input from the command line
When a user types a message, it's added to the conversation history and sent to the agent
The agent processes the request using the invoke() method with the full conversation history
Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

What's happening:

We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Uploadcare and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['uploadcare']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "uploadcare-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Uploadcare related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    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;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Uploadcare through Composio's Tool Router.

Key features of this implementation:

Dynamic tool loading through Composio's Tool Router
Conversation history maintenance for context-aware responses
Async Python provides clean, efficient execution of agent workflows

You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

TOOLS

Supported Tools

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

Check AWS Rekognition Moderation Status

Tool to check the execution status of AWS Rekognition Moderation labels detection.

Check Remove.bg Status

Tool to check Remove.

Copy Uploadcare File to Local Storage

Tool to copy a file to local storage within the same Uploadcare project.

Create File Group (Upload API)

Tool to create a file group from already uploaded files using Uploadcare's Upload API.

Create Uploadcare webhook

Create a new webhook subscription to receive notifications when file events occur.

Delete File Metadata Key

Tool to delete a specific metadata key from an Uploadcare file.

Batch Delete Uploadcare Files

Tool to delete multiple files from Uploadcare storage in a single request.

Delete Uploadcare Group

Tool to delete a file group.

Delete Uploadcare File

Tool to delete a single file from Uploadcare storage by UUID.

Delete Uploadcare Webhook

Permanently deletes a webhook subscription from your Uploadcare project.

Delete Uploadcare Webhook by URL

Tool to delete a webhook subscription by its target URL.

Execute ClamAV virus scan

Tool to execute ClamAV virus scan on an uploaded file.

Get AWS Rekognition Execution Status

Tool to check AWS Rekognition execution status for label detection.

Get ClamAV Scan Status

Tool to check the execution status of a ClamAV virus scan.

Get File Group Info (Upload API)

Tool to get information about a file group from the Upload API.

Get Uploadcare File Info

Tool to get information about a specific file.

Get File Metadata

Tool to retrieve all metadata key-value pairs associated with an Uploadcare file.

Get File Metadata Key Value

Tool to get the value of a specific metadata key for an Uploadcare file.

Get Uploadcare Group Info

Tool to get information about a specific file group.

Get Uploadcare Project Info

Tool to get information about the current Uploadcare project.

Get Uploaded File Info

Tool to get information about an uploaded file using Uploadcare's Upload API.

Get URL Upload Status

Tool to check the status of a URL upload task.

Mirror Uploadcare Image

Tool to mirror an image horizontally via Uploadcare CDN.

List Uploadcare Files

List files in an Uploadcare project with pagination and optional filtering.

List Uploadcare Groups

Tool to list groups in the project.

List Uploadcare Webhooks

Retrieves all webhook subscriptions for the authenticated Uploadcare project.

Rotate Image

Tool to rotate an image by specified degrees counterclockwise.

Start Multipart Upload

Tool to start a multipart upload session for files larger than 100MB.

Batch Store Files

Tool to store multiple files in one request.

Store Uploadcare File

Tool to mark an Uploadcare file as permanently stored.

Store Single Uploadcare File

Tool to store a single file by UUID permanently.

Update File Metadata Key

Tool to update or set the value of a specific metadata key for a file.

Update Uploadcare webhook

Update an existing webhook subscription by its ID.

Upload File from URL

Tool to upload a file from a publicly available URL to Uploadcare.

FRAMEWORKS

How to build Uploadcare MCP Agent with another framework

OpenAI Agents SDK

Use Uploadcare MCP with OpenAI Agents SDK

Claude Agent SDK

Use Uploadcare MCP with Claude Agent SDK

Claude Code

Use Uploadcare MCP with Claude Code

Claude Cowork

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Codex

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OpenClaw

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Hermes

Use Uploadcare MCP with Hermes

CLI

Use Uploadcare MCP with CLI

Google ADK

Use Uploadcare MCP with Google ADK

Vercel AI SDK

Use Uploadcare MCP with Vercel AI SDK

Mastra AI

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LlamaIndex

Use Uploadcare MCP with LlamaIndex

CrewAI

Use Uploadcare MCP with CrewAI

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

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Google Docs

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Google Super

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Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization.

Affinda

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Affinda is an AI-powered document processing platform that automates data extraction from resumes, invoices, and more. It streamlines document-heavy workflows by turning files into structured, actionable data.

FAQ

Frequently asked questions

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

Yes, you can. LangChain 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 Uploadcare tools.

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

Start with Uploadcare.It takes 30 seconds.

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

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Customer stories

Teams ship real agents on Composio

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Uploadcare MCP with LangChain

Connect Uploadcare without auth hassles

Introduction

Also integrate Uploadcare with

TL;DR

What is LangChain?

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

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Initialize Composio client

Create a Tool Router session

Configure the agent with the MCP URL

Set up interactive chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Uploadcare MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Google Drive

Google Docs

Google Super

Affinda

Frequently asked questions

What are the differences in Tool Router MCP and Uploadcare MCP?+

Can I use Tool Router MCP with LangChain?+

Can I manage the permissions and scopes for Uploadcare while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Uploadcare.It takes 30 seconds.

Teams ship real agents on Composio