TweekIT MCP Server - Ingest and Convert Just About Any Filetype Into AI Workflows

Overview

TweekIT MCP Server is the universal media translator for AI workflows, making any file ready for processing in seconds. Built on the robust content processing engine of Equilibrium's MediaRich Server, a technology developed since 2000 and trusted by massive portals and media companies worldwide, TweekIT brings decades of expertise in handling complex media, drawing on a pedigree that includes the renowned DeBabelizer.

With TweekIT, you can upload, preview, transform, and download over 400 supported file types using a consistent API or widget interface. It removes the pain of unpredictable input formats by automatically normalizing and preparing assets for the next step in your workflow.

What is TweekIT?

TweekIT is a universal media ingestion and transformation service designed to take any supported file and make it AI ready in seconds. Whether you are normalizing formats, resizing assets, or extracting a single page from a complex document, TweekIT provides a consistent, API first way to get exactly the output you need without worrying about the quirks of individual file types.

Why use it in an MCP context?

In a Model Context Protocol (MCP) workflow, TweekIT acts like a universal translator for media. It sits between your AI agent and the unpredictable real world files it encounters, ensuring every asset is transformed into a compatible, standardized format before processing. This is similar to how GitHub Actions streamlines software automation, but applied to media handling in AI pipelines.

With TweekIT in your MCP toolset, your agents can:

  • Accept a wider range of inputs from users without failure
  • Automatically apply transformations such as cropping, resizing, format conversion, and background changes
  • Pass clean, ready to use assets to the next step in your AI workflow with no manual intervention fixing the constant customer file ingestion failures we are all to familiar with

Example scenario

A user uploads a scanned PDF of an ID card as part of an onboarding process. Your MCP agent calls TweekIT to:

  1. Convert the PDF to a PNG image
  2. Crop to just the ID card
  3. Resize to a standard 300x300 pixel headshot
  4. Return the transformed image directly into the verification pipeline

The entire process happens in seconds, and your workflow never sees an incompatible file format.

Key Capabilities

  • Supports 450+ file types for seamless ingestion and conversion, leveraging a core engine refined over two decades to handle dynamic imaging and video delivery.
  • Stateless and API first design for fast, scalable integrations
  • Widget or REST API access to fit any application architecture
  • Enterprise grade security with secure key handling and short lived asset storage
  • Instant compatibility fixes that prevent AI pipeline failures from bad input formats immediately

Try it now:

  • Live Demo – Upload and transform files in your browser
  • View Use Case Examples for real workflows and code samples on the website. The specific MCP manifest conversions are shown in section 7 below.

Requirements

  • Python 3.10 or later
  • Docker (optional, for containerized builds)
  • httpx library for HTTP requests
  • FastMCP for tool registration and server functionality

Installation

Clone the repository:

git clone https://github.com/your-username/mcpserver.git
cd mcpserver

Install dependencies

pip install -r requirements.txt

Set up environment variables:

PORT: The port on which the server will run (default: 8080).

Quickstart

Step 1: Sign Up

Create your free TweekIT account and get started with 10,000 API calls included at no cost.

Pricing and Signup here to access your API credentials and start using the service.

Step 2: Choose Your Authentication Method

TweekIT supports multiple authentication methods. Both work with the MCP integration.

  • AppID – Fastest way to get started for quick tests and prototyping
  • API Key and Secret – Recommended for production use, more secure and easier to control access

You will find these values in your account dashboard after sign up. Keep them safe and never expose them in client-side code.

Step 3: Make Your First API Call

Below is a minimal working Node.js example that uploads an image, previews the transformation, and downloads the result. This example uses API Key and Secret authentication.

const fetch = require('node-fetch');
const fs = require('fs');
const FormData = require('form-data');

const headers = {
  apikey: '{Your API Key}',
  apisecret: '{Your API Secret}'
};

async function uploadFile(filePath, fileName) {
  const url = 'https://www.tweekit.io/tweekit/api/image/upload';
  const formData = new FormData();
  formData.append('name', fileName);
  formData.append('file', fs.createReadStream(filePath));

  const response = await fetch(url, { method: 'POST', headers, body: formData });
  const docID = response.headers.get('x-tweekit-docid');
  return docID;
}

async function previewImage(docID) {
  const url = `https://www.tweekit.io/tweekit/api/image/preview/${docID}`;
  const options = {
    method: 'POST',
    headers: { ...headers, 'Content-Type': 'application/json;charset=UTF-8' },
    body: JSON.stringify({ width: 300, height: 300, fmt: 'png' })
  };
  const response = await fetch(url, options);
  const buffer = await response.buffer();
  fs.writeFileSync('output.png', buffer);
}

(async () => {
  const docID = await uploadFile('example.jpg', 'example.jpg');
  await previewImage(docID);
  console.log('Transformation complete. File saved as output.png');
})();

Step 4: See It in Action

You can explore TweekIT visually before writing any code. The live demo lets you upload files, apply transformations, and download the results instantly.

Open the Live Demo

View Use Case Examples for real workflows and code samples