How to integrate Encodian MCP with Vercel AI SDK v6

This guide walks you through connecting Encodian to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Encodian agent that can resize all images in project folder, extract author and page count from pdf, add custom header to every pdf file through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Encodian account through Composio's Encodian MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Introduction

This guide walks you through connecting Encodian to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Encodian agent that can resize all images in project folder, extract author and page count from pdf, add custom header to every pdf file through natural language commands.

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

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

Also integrate Encodian with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • How to set up and configure a Vercel AI SDK agent with Encodian integration
  • Using Composio's Tool Router to dynamically load and access Encodian tools
  • Creating an MCP client connection using HTTP transport
  • Building an interactive CLI chat interface with conversation history management
  • Handling tool calls and results within the Vercel AI SDK framework

What is Vercel AI SDK?

The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state.

Key features include:

  • streamText: Core function for streaming responses with real-time tool support
  • MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp
  • Step Counting: Control multi-step tool execution with stopWhen: stepCountIs()
  • OpenAI Provider: Native integration with OpenAI models

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

The Encodian MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Encodian account. It provides structured and secure access to your Encodian document automation suite, so your agent can perform actions like managing files, processing PDFs, encoding or decoding content, and automating workflow tasks on your behalf.

  • File management and property retrieval: Quickly get detailed information about files, move documents between containers, and keep your Microsoft 365 storage organized automatically.
  • Document processing and automation: Direct your agent to add headers and footers to PDFs, extract PDF metadata, or resize images for seamless document formatting and compliance tasks.
  • Base64 content conversion: Effortlessly encode text or files to Base64, or decode Base64 strings back to usable files for secure data exchange and workflow integration.
  • Archive extraction and manipulation: Unzip files and retrieve their contents, making it easy to automate bulk document handling or trigger downstream processing steps.
  • Data integrity and comparison tools: Use hashing and text comparison utilities to verify file integrity, detect changes, or ensure consistency across your documents 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:

  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 you begin, make sure you have:
  • Node.js and npm installed
  • A Composio account with API key
  • An OpenAI API key
2

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.
3

Install required dependencies

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

First, install the necessary packages for your project.

What you're installing:

  • @ai-sdk/openai: Vercel AI SDK's OpenAI provider
  • @ai-sdk/mcp: MCP client for Vercel AI SDK
  • @composio/core: Composio SDK for tool integration
  • ai: Core Vercel AI SDK
  • dotenv: Environment variable management
4

Set up environment variables

bash
OPENAI_API_KEY=your_openai_api_key_here
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here

Create a .env file in your project root.

What's needed:

  • OPENAI_API_KEY: Your OpenAI API key for GPT model access
  • COMPOSIO_API_KEY: Your Composio API key for tool access
  • COMPOSIO_USER_ID: A unique identifier for the user session
5

Import required modules and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

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

if (!process.env.OPENAI_API_KEY) 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,
});
What's happening:
  • We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio
  • The dotenv/config import automatically loads environment variables
  • The MCP client import enables connection to Composio's tool server
6

Create Tool Router session and initialize MCP client

typescript
async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["encodian"],
  });

  const mcpUrl = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Encodian tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned mcp object contains the URL and authentication headers needed to connect to the MCP server
  • This session provides access to all Encodian-related tools through the MCP protocol
7

Connect to MCP server and retrieve tools

typescript
const mcpClient = await createMCPClient({
  transport: {
    type: "http",
    url: mcpUrl,
    headers: session.mcp.headers, // Authentication headers for the Composio MCP server
  },
});

const tools = await mcpClient.tools();
What's happening:
  • We're creating an MCP client that connects to our Composio Tool Router session via HTTP
  • The mcp.url provides the endpoint, and mcp.headers contains authentication credentials
  • The type: "http" is important - Composio requires HTTP transport
  • tools() retrieves all available Encodian tools that the agent can use
8

Initialize conversation and CLI interface

typescript
let messages: ModelMessage[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log(
  "Ask any questions related to encodian, like summarize my last 5 emails, send an email, etc... :)))\n",
);

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

rl.prompt();
What's happening:
  • We initialize an empty messages array to maintain conversation history
  • A readline interface is created to accept user input from the command line
  • Instructions are displayed to guide the user on how to interact with the agent
9

Handle user input and stream responses with real-time tool feedback

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

  try {
    const stream = streamText({
      model: openai("gpt-5"),
      messages,
      tools,
      toolChoice: "auto",
      stopWhen: stepCountIs(10),
      onStepFinish: (step) => {
        for (const toolCall of step.toolCalls) {
          console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

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

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • We use streamText instead of generateText to stream responses in real-time
  • toolChoice: "auto" allows the model to decide when to use Encodian tools
  • stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations
  • onStepFinish callback displays which tools are being used in real-time
  • We iterate through the text stream to create a typewriter effect as the agent responds
  • The complete response is added to conversation history to maintain context
  • Errors are caught and displayed with helpful retry suggestions

Complete Code

Here's the complete code to get you started with Encodian and Vercel AI SDK:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

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

if (!process.env.OPENAI_API_KEY) 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,
});

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["encodian"],
  });

  const mcpUrl = session.mcp.url;

  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      url: mcpUrl,
      headers: session.mcp.headers, // Authentication headers for the Composio MCP server
    },
  });

  const tools = await mcpClient.tools();

  let messages: ModelMessage[] = [];

  console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
  console.log(
    "Ask any questions related to encodian, like summarize my last 5 emails, send an email, etc... :)))\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({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    try {
      const stream = streamText({
        model: openai("gpt-5"),
        messages,
        tools,
        toolChoice: "auto",
        stopWhen: stepCountIs(10),
        onStepFinish: (step) => {
          for (const toolCall of step.toolCalls) {
            console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

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

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

Conclusion

You've successfully built a Encodian agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.

Key features of this implementation:

  • Real-time streaming responses for a better user experience with typewriter effect
  • Live tool execution feedback showing which tools are being used as the agent works
  • Dynamic tool loading through Composio's Tool Router with secure authentication
  • Multi-step tool execution with configurable step limits (up to 10 steps)
  • Comprehensive error handling for robust agent execution
  • Conversation history maintenance for context-aware responses

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

Supported Tools

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

Add Attachments to PDF

Tool to add file attachments to a PDF document.

Add Image Watermark to PDF

Tool to add an image watermark to a PDF document.

Add Image Watermark to PDF (Advanced)

Tool to add an advanced image watermark to a PDF with precise control over positioning, opacity, scale, quality, and rotation.

Array Add Items

Tool to add items to a JSON array at a specified position (first, last, or specific index).

Create ZIP Archive

Tool to create a ZIP archive from multiple documents.

Apply AI OCR to PDF

Tool to apply AI-powered OCR to a PDF document with optional preprocessing filters.

Apply OCR to PDF (Standard)

Tool to apply standard OCR to a PDF document with optional preprocessing filters.

Decode Base64 String

Tool to decode a Base64 string to a file.

Base64 Encode

Tool to encode a string to Base64.

Calculate Date

Tool to calculate a date by adding or subtracting a time interval from a given date.

Check Array Contains Value

Tool to check if a value exists within a JSON array.

Check Text Contains Value

Tool to check if a text string contains a specific value with configurable comparison rules.

Clean String

Tool to clean text by removing control characters, invalid filename characters, and custom character sets.

Clean Up Photo Image

Tool to clean up photo images by removing artifacts, correcting orientation, and enhancing quality.

Combine Arrays

Tool to combine two JSON arrays by matching a key attribute.

Compare Text

Tool to compare two text strings and determine if they match.

Compare Word Documents

Tool to compare two Microsoft Word or PDF documents and generate a document with tracked changes.

Compress Image

Tool to compress an image in JPG or PNG format.

Compress PDF

Tool to compress a PDF document by optimizing images, removing unused objects, and applying various compression techniques.

Concatenate Text

Tool to concatenate an array of text values with an optional delimiter.

Array to JSON

Tool to convert an array to a named JSON object.

Array to XML

Tool to convert a JSON array to XML format.

Convert File to PDF

Tool to convert a file to PDF format.

Convert HTML to Image

Tool to convert HTML content to an image.

Convert HTML to PDF (V2)

Tool to convert HTML content or a URL to PDF format (V2).

Convert HTML to Word

Tool to convert HTML content to Word (DOCX) format.

Convert Image to Grayscale

Tool to convert an image to grayscale.

Convert Image to PDF

Tool to convert an image file to PDF format with optional OCR.

Convert JSON to Excel

Tool to convert JSON data to Excel format.

Convert JSON to XML

Tool to convert JSON data to XML format.

Convert Time Zone

Tool to convert a date and time value from one time zone to another using Encodian's time zone conversion API.

Convert XML to JSON

Tool to convert XML strings to JSON format.

Count Array Items

Tool to count the number of items in a JSON array or object.

Create QR Code

Tool to generate a QR code barcode image with customizable size, colors, border, and encoding options.

Format Text Case

Tool to format text with various case transformations (uppercase, lowercase, title case, etc.

Hash Data

Tool to compute a cryptographic hash (MD5, SHA256, etc.

Unzip File

Extracts all files from a ZIP archive and returns their base64-encoded contents.

Get Convert Excel Schema

Tool to retrieve the dynamic schema for Excel conversion operations.

Get Convert Word Schema

Tool to retrieve the dynamic JSON schema for Word document conversion operations.

Get Convert CAD Schema

Tool to retrieve the dynamic schema for CAD file conversion operations.

Get Convert Image to PDF Schema

Tool to retrieve the dynamic schema for Convert - Image to PDF operations.

Get Convert PowerPoint Schema

Tool to retrieve the dynamic schema for PowerPoint conversion operations.

Get Convert Visio Schema

Tool to retrieve the dynamic schema for Visio file conversion.

Get Create Barcode Schema

Tool to retrieve the dynamic schema for creating a barcode.

Get Crop Image Schema

Tool to retrieve the dynamic schema for the Crop Image action.

Get Dynamic Schema for HTTP Request

Tool to retrieve the dynamic schema for the HTTP Request utility based on authentication type.

Get Word Insert Text Schema

Tool to retrieve the dynamic schema for Word Insert Text operations.

Get File Properties

Tool to retrieve properties of a file.

Get Operation Status for AIRunPromptText

Tool to get the operation status of an AIRunPromptText operation.

Get Operation Status for Encodian Send to Filer

Tool to get the operation status for an Encodian Send to Filer operation.

Get Operation Status Extract Image

Tool to retrieve the operation status of a PDF ExtractImage operation.

Get Operation Status for ExtractTextRegion

Tool to retrieve the operation status of an ExtractTextRegion operation.

Get Operation Status File Only

Tool to retrieve operation status for file-only operations.

Get Operation Status for Image Extract Text

Tool to get the operation status of an ImageExtractText operation.

Get Operation Status for Multiple Files

Tool to retrieve the operation status of a Word MultipleFiles operation.

Get Operation Status - PDF Split Barcode

Tool to retrieve operation status for a PDF split barcode operation.

Get Operation Status for Split Document

Tool to retrieve the operation status of a PDF SplitDocument operation.

Get Sign PDF Schema

Tool to retrieve the dynamic schema for PDF signing operations.

Get Subscription Status

Tool to retrieve Encodian subscription status for Flowr and Vertr.

Resize Image

Tool to resize an image by percentage or dimensions.

Move File

Tool to move a file between containers.

Add PDF Header Footer

Tool to add HTML header and footer to a PDF.

Get PDF Metadata

Extract comprehensive metadata and properties from PDF documents.

Watermark PDF

Tool to apply a text watermark to a PDF.

Read QR Code from Document

Tool to read QR codes from PDF or DOCX documents.

Word - Replace Text With Image

Tool to replace text with an image in a Word document.

Validate Email Address

Validates an email address string against a custom regex pattern using Encodian's validation API.

Validate URL Availability

Tool to validate the availability of a specified URL.

Write Range to Excel

Tool to write values to a cell range in an Excel worksheet.

FRAMEWORKS

How to build Encodian MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Encodian MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Encodian MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Encodian MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Encodian MCP with Claude Cowork

Codex logo

Codex

Use Encodian MCP with Codex

OpenClaw logo

OpenClaw

Use Encodian MCP with OpenClaw

Hermes logo

Hermes

Use Encodian MCP with Hermes

CLI logo

CLI

Use Encodian MCP with CLI

Google ADK logo

Google ADK

Use Encodian MCP with Google ADK

LangChain logo

LangChain

Use Encodian MCP with LangChain

Mastra AI logo

Mastra AI

Use Encodian MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Encodian MCP with LlamaIndex

CrewAI logo

CrewAI

Use Encodian MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, you can. Vercel AI SDK v6 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 Encodian tools.

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

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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
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
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
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
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
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
Jerome Leclanche
Co-Founder, Ingram Technologies