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AI MCP Workflows with TweekIT

Use TweekIT’s hosted MCP server to normalize any incoming file into AI‑ready formats inside your agents and automations. This prevents pipeline failures and removes manual pre‑processing.

Hosted endpoint: https://mcp.tweekit.io/mcp/

Common Workflows

  • Image‑to‑Image: Convert any file (incl. first page of PDFs, PSD/AI, RAW) to PNG/JPG for model inputs.
  • OCR Pipelines: Convert documents to high‑contrast PNGs for better text recognition.
  • Office → PDF: Normalize Word/PowerPoint/Visio and legacy docs into standard PDFs for LLM ingestion.
  • Pro Formats: Safely render Illustrator/complex PDFs into images when direct ingestion fails.

Quickstarts

Claude Desktop

{
  "mcpServers": {
    "tweekit": {
      "transport": { "type": "http", "url": "https://mcp.tweekit.io/mcp/" }
    }
  }
}

Call convert with base64 content (shortened):

{
  "name": "convert",
  "arguments": {
    "apiKey": "YOUR_KEY",
    "apiSecret": "YOUR_SECRET",
    "inext": "png",
    "outfmt": "webp",
    "blob": "<base64>",
    "width": 300,
    "height": 300
  }
}

ChatGPT MCP

{ "name": "search", "arguments": { "query": "tweekit", "max_results": 3 } }
{ "name": "fetch",  "arguments": { "url": "https://tweekit.io" } }

OpenAI TypeScript (MCP SDK)

import { Client } from "@modelcontextprotocol/sdk/client";
import { HttpClientTransport } from "@modelcontextprotocol/sdk/client/transport/http";

const transport = new HttpClientTransport(new URL("https://mcp.tweekit.io/mcp/"));
const client = new Client({ name: "tweekit-example", version: "1.0.0" }, { capabilities: {} }, transport);
await client.connect();
const tools = await client.listTools();
const res = await client.callTool({ name: "search", arguments: { query: "tweekit", max_results: 3 } });
console.log(res);

Python Quick Call

import asyncio
from fastmcp import Client

async def main():
    async with Client("https://mcp.tweekit.io/mcp/") as c:
        print(await c.list_tools())
        out = await c.call_tool("fetch", {"url": "https://tweekit.io"})
        print(out)

asyncio.run(main())

Next Steps