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How to integrate Pandadoc MCP with Vercel AI SDK v6

Connect Vercel AI SDK v6 to Pandadoc MCP. Create a new contract from pdf upload, add an attachment to a draft proposal, and more using natural language, with authentication handled for you.

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Pandadoc

Api Key

Pandadoc is a document automation platform for creating, sending, and e-signing proposals and contracts. It streamlines sales workflows and speeds up agreement processes.

111 Tools

Managed auth

Connect Pandadoc without auth hassles

We manage OAuth, API keys, token refresh, and scopes — you just build.

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Explore the MCP Gateway

Introduction

This guide walks you through connecting Pandadoc to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Pandadoc agent that can create documents from file uploads, manage templates, organize folders, update contacts, and search catalog items through natural language commands.

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

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

For exact tool slugs and parameter tables, see the tool catalog in the Composio docs.

Also integrate Pandadoc with

Claude Code Claude Cowork OpenAI Agents SDK Claude Agent SDK Codex OpenClaw Hermes Atomic Agent Google ADK LangChain Mastra AI LlamaIndex CrewAI Pydantic AI AutoGen

TL;DR

Here's what you'll learn:

How to set up and configure a Vercel AI SDK agent with Pandadoc integration
Using Composio's Tool Router to dynamically load and access Pandadoc 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 Pandadoc MCP server, and what's possible with it?

The Pandadoc MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Pandadoc account. It provides structured and secure access to your documents, templates, contacts, and workflows, so your agent can perform actions like creating documents, managing templates, organizing folders, and handling contacts on your behalf.

Automated document creation and uploads: Have your agent generate new contracts, proposals, or agreements by uploading files or leveraging templates—ready for processing and e-signature in Pandadoc.
Template management and customization: Let your agent create, update, or delete templates, making it easy to standardize and scale your document workflows across teams.
Contact creation and maintenance: Seamlessly add, update, or delete contacts in your Pandadoc account, ensuring your address book stays organized and always up to date.
Folder and document organization: Ask your agent to create structured folders, move documents, or attach supplemental files to keep your workspace tidy and accessible.
Webhook setup for workflow automation: Empower your agent to create Pandadoc webhooks, so you can receive instant notifications about document status changes, completions, or updates—no manual checking required.

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 step09 STEPS

Prerequisites

Before you begin, make sure you have:

Node.js and npm installed
A Composio account with API key
An OpenAI API key

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 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

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

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

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: ["pandadoc"],
  });

  const mcpUrl = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Pandadoc 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 Pandadoc-related tools through the MCP protocol

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 Pandadoc tools that the agent can use

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 pandadoc, 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

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 Pandadoc 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 Pandadoc 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: ["pandadoc"],
  });

  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 pandadoc, 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 Pandadoc 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 Pandadoc action and event your agent gets out of the box.

Add a document recipient

Add a document recipient.

Add a workspace member

Add a workspace member.

Append a content library item to a document

Append a content library item to a document.

Bulk-delete documents

Bulk-delete documents.

Change document ownership

Change document ownership.

Change document status

Change document status.

Change Document Status with Upload

Manually change a document's status with an optional file attachment.

Change a workspace member role

Change a workspace member role.

Create a content library item

Create a content library item.

Create Content Library Item from File Upload

Upload a file to create a PandaDoc content library item asynchronously.

Create Document Attachment

Creates and adds an attachment to a PandaDoc document.

Create a document editing session

Create a document editing session.

Create document fields

Create document fields.

Create Document from File Upload

Creates a new document in PandaDoc by uploading a file (PDF, DOCX, or RTF).

Create a document section

Create a document section.

Create Document Section from File Upload

Add a section to an existing version 2 document from a PDF, DOCX, or RTF.

Create an embedded signing session

Create an embedded signing session.

Create Document Folder

Creates a new folder in PandaDoc to organize documents.

Create a linked object

Create a linked object.

Create a notarization request

Create a notarization request.

Create or Update Contact

Create a PandaDoc contact or attempt to update an existing contact by email.

Create a product catalog item

Create a product catalog item.

Create Template

This tool allows users to create a new template in PandaDoc from a PDF file or from scratch.

Create a template editing session

Create a template editing session.

Create a template folder

Create a template folder.

Create a user

Create a user.

Create PandaDoc Webhook

Creates a new webhook subscription in PandaDoc to receive notifications about specific events.

Create a workspace

Create a workspace.

Deactivate a workspace

Deactivate a workspace.

Delete Contact

This tool allows you to delete a contact from your PandaDoc account.

Delete a document

Delete a document.

Delete a document attachment

Delete a document attachment.

Delete a document recipient

Delete a document recipient.

Delete a document section

Delete a document section.

Delete a linked object

Delete a linked object.

Delete a notarization request

Delete a notarization request.

Delete a product catalog item

Delete a product catalog item.

Delete Template

This tool deletes a specific template from PandaDoc.

Delete a webhook subscription

Delete a webhook subscription.

Download a completed document

Download a completed document.

Download Document

Download a PandaDoc document as PDF, or a bundle as separate PDFs in a ZIP.

Download a document attachment

Download a document attachment.

Duplicate a template

Duplicate a template.

Get API log details

Get API log details.

Get attachment details

Get attachment details.

Get automatic reminder settings

Get automatic reminder settings.

Get automatic reminder status

Get automatic reminder status.

Get contact details

Get contact details.

Get content library item details

Get content library item details.

Get content library item status

Get content library item status.

Get the current member

Get the current member.

Get Document Details

Fetch detailed metadata for a specific PandaDoc document including recipients, fields/tokens values, pricing data, metadata, tags, and content-block names.

Get the document eSign disclosure

Get the document eSign disclosure.

Get document section details

Get document section details.

Get document settings

Get document settings.

Get document status

Get document status.

Get member details

Get member details.

Get notarization request details

Get notarization request details.

Get a product catalog item

Get a product catalog item.

Get section upload status

Get section upload status.

Get Template Details

Retrieve details for a specific PandaDoc template by ID, including metadata, roles, fields, tokens and pricing information when available.

Get template settings

Get template settings.

Get template sharing settings

Get template sharing settings.

Get template status

Get template status.

Get a user by ID

Get a user by ID.

Get webhook event details

Get webhook event details.

Get webhook subscription details

Get webhook subscription details.

List API logs

List API logs.

List Contacts

List PandaDoc workspace contacts, optionally filtering by email address.

List content library items

List content library items.

List document attachments

List document attachments.

List document audit trail

List document audit trail.

List document fields

List document fields.

List Document Folders

List PandaDoc document folders, optionally specifying a parent folder and pagination.

List Documents

List and search PandaDoc documents with filters, pagination, and ordering.

List documents by linked object

List documents by linked object.

List document sections

List document sections.

List forms

List forms.

List linked objects

List linked objects.

List notaries

List notaries.

List notarization requests

List notarization requests.

List recent SMS opt-outs

List recent SMS opt-outs.

List template folders

List template folders.

List Templates

This tool retrieves a list of all templates available in the PandaDoc account.

List users

List users.

List webhook events

List webhook events.

List webhook subscriptions

List webhook subscriptions.

List workspace members

List workspace members.

List workspaces

List workspaces.

Move a document to draft

Move a document to draft.

Move Document to Folder

This tool allows users to move a document to a specific folder within their PandaDoc account.

Reassign a document signer

Reassign a document signer.

Remove a workspace member

Remove a workspace member.

Rename a document folder

Rename a document folder.

Rename a template folder

Rename a template folder.

Search Catalog Items

Search PandaDoc product catalog items with filters and ordering.

Search product catalog items

Search product catalog items.

Send a document

Send a document.

Send a manual reminder

Send a manual reminder.

Transfer ownership of all documents

Transfer ownership of all documents.

Update automatic reminder settings

Update automatic reminder settings.

Update a document

Update a document.

Update document field assignments

Update document field assignments.

Update a document quote

Update a document quote.

Update a document recipient

Update a document recipient.

Update document settings

Update document settings.

Update a product catalog item

Update a product catalog item.

Update a template

Update a template.

Update template settings

Update template settings.

Update template sharing settings

Update template sharing settings.

Update a webhook subscription

Update a webhook subscription.

FRAMEWORKS

How to build Pandadoc MCP Agent with another framework

Claude Code

Use Pandadoc MCP with Claude Code

Claude Cowork

Use Pandadoc MCP with Claude Cowork

OpenAI Agents SDK

Use Pandadoc MCP with OpenAI Agents SDK

Claude Agent SDK

Use Pandadoc MCP with Claude Agent SDK

Codex

Use Pandadoc MCP with Codex

OpenClaw

Use Pandadoc MCP with OpenClaw

Hermes

Use Pandadoc MCP with Hermes

Atomic Agent

Use Pandadoc MCP with Atomic Agent

Google ADK

Use Pandadoc MCP with Google ADK

LangChain

Use Pandadoc MCP with LangChain

Mastra AI

Use Pandadoc MCP with Mastra AI

LlamaIndex

Use Pandadoc MCP with LlamaIndex

CrewAI

Use Pandadoc MCP with CrewAI

Pydantic AI

Use Pandadoc MCP with Pydantic AI

AutoGen

Use Pandadoc MCP with AutoGen

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Google Drive

Oauth2

Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.

Google Docs

Oauth2

Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze.

Google Super

Oauth2Api Key

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.

ActiveMerge

Api Key

ActiveMerge is a document automation platform for generating documents, images, merged files, and e-signature workflows. It helps teams turn templates and stored files into finished, shareable documents faster.

FAQ

Frequently asked questions

With a standalone Pandadoc MCP server, the agents and LLMs can only access a fixed set of Pandadoc tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Pandadoc 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 Pandadoc tools.

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

Start with Pandadoc.It takes 30 seconds.

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

Start building

How to integrate Pandadoc MCP with Vercel AI SDK v6

Connect Pandadoc without auth hassles

Introduction

Also integrate Pandadoc with

TL;DR

What is Vercel AI SDK?

What is the Pandadoc 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 required dependencies

Set up environment variables

Import required modules and validate environment

Create Tool Router session and initialize MCP client

Connect to MCP server and retrieve tools

Initialize conversation and CLI interface

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

Complete Code

Conclusion

Supported Tools

How to build Pandadoc MCP Agent with another framework

Claude Code

Claude Cowork

OpenAI Agents SDK

Claude Agent SDK

Codex

OpenClaw

Hermes

Atomic Agent

Google ADK

LangChain

Mastra AI

LlamaIndex

CrewAI

Pydantic AI

AutoGen

Explore Other Toolkits

Google Drive

Google Docs

Google Super

ActiveMerge

Frequently asked questions

What are the differences in Tool Router MCP and Pandadoc MCP?

Can I use Tool Router MCP with Vercel AI SDK v6?

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

How safe is my data with Composio Tool Router?

Start with Pandadoc.It takes 30 seconds.