How to integrate Confluence MCP with Vercel AI SDK v6

This guide walks you through connecting Confluence to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Confluence agent that can create a project documentation page in marketing space, add 'urgent' label to q3 planning page, publish team meeting summary as a blog post through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Confluence account through Composio's Confluence MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Confluence

Oauth2S2s Oauth2Api Key

Confluence is Atlassian's team collaboration and knowledge management platform. It helps your team organize, share, and update documents and project content in one secure workspace.

62 Tools23 Triggers

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Introduction

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

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

Also integrate Confluence with

ChatGPT OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenCode Cursor VS Code OpenClaw Hermes CLI Google ADK LangChain Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

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

The Confluence MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Confluence account. It provides structured and secure access to your Confluence spaces, pages, and content, so your agent can perform actions like creating pages, publishing blog posts, organizing spaces, and managing metadata on your behalf.

Automated page and space creation: Instantly create new Confluence pages or entire spaces, empowering your agent to generate project documentation, wikis, or knowledge bases as needed.
Effortless blog post publishing: Let your agent draft and publish new blog posts within specified Confluence spaces to keep your team up-to-date and share knowledge seamlessly.
Content labeling and metadata management: Have your agent add labels and custom properties to pages, blog posts, or spaces, making it easy to organize, tag, and categorize information for better discoverability.
Private space setup and management: Direct your agent to create private, isolated workspaces for sensitive projects or teams, ensuring only authorized collaborators have access.
Custom content property automation: Empower your agent to attach or update custom metadata on pages, blog posts, spaces, or whiteboards, streamlining your internal documentation 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 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: ["confluence"],
  });

  const mcpUrl = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Confluence 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 Confluence-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 Confluence 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 confluence, 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 Confluence 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 Confluence 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: ["confluence"],
  });

  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 confluence, 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 Confluence 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 & TRIGGERS

Supported Tools and Triggers

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

Add Content Label

Tool to add labels to a piece of content.

CQL Search

Searches for content in Confluence using Confluence Query Language (CQL).

Create Blogpost

Tool to create a new Confluence blog post.

Create Blogpost Property

Tool to create a property on a specified blog post.

Create Whiteboard Property

Tool to create a new content property on a whiteboard.

Create Footer Comment

Tool to create a footer comment on a Confluence page, blog post, attachment, or custom content.

Create Page

Tool to create a new Confluence page in a specified space.

Create Page Property

Tool to create a property on a Confluence page.

Create Private Space

Tool to create a private Confluence space.

Create Space

Tool to create a new Confluence space.

Create Space Property

Tool to create a new property on a Confluence space.

Create Whiteboard

Tool to create a new Confluence whiteboard.

Delete Blogpost Property

Tool to delete a blog post property.

Delete Page Content Property

Tool to delete a content property from a page by property ID.

Delete Whiteboard Content Property

Tool to delete a content property from a whiteboard by property ID.

Delete Page

Tool to delete a Confluence page.

Delete Space

Tool to delete a Confluence space by its key.

Delete Space Property

Tool to delete a space property.

Download Attachment

Downloads an attachment from a Confluence page and returns a publicly accessible S3 URL.

Get Attachment Labels

Tool to list labels on an attachment.

Get Attachments

Tool to retrieve attachments of a Confluence page.

Get Audit Logs

Tool to retrieve Confluence audit records.

Get Blogpost by ID

Tool to retrieve a specific Confluence blog post by its ID.

Get Blogpost Labels

Tool to retrieve labels of a specific Confluence blog post by ID.

Get Blogpost Like Count

Tool to get like count for a Confluence blog post.

Get Blogpost Operations

Tool to retrieve permitted operations for a Confluence blog post.

Get Blog Posts

Tool to retrieve a list of blog posts.

Get Blog Posts For Label

Tool to list all blog posts under a specific label.

Get Blogpost Version Details

Tool to retrieve details for a specific version of a blog post.

Get Blogpost Versions

Tool to retrieve all versions of a specific blog post.

Get Child Pages

Tool to list all direct child pages of a given Confluence page.

Get Blog Post Content Properties

Tool to retrieve all content properties on a blog post.

Get Page Content Properties

Tool to retrieve all content properties on a page.

Get Content Restrictions

Tool to retrieve restrictions on a Confluence content item.

Get Current User

Tool to get information about the currently authenticated user — always scoped to the account tied to the configured connection, not arbitrary users.

Get Inline Comments for Blog Post

Tool to retrieve inline comments for a Confluence blog post.

Get Labels

Tool to retrieve all labels in a Confluence site; use for label discovery when you need to list or page through labels.

Get Page Labels

Tool to retrieve labels of a specific Confluence page by ID.

Get Labels for Space

Tool to list labels on a space.

Get Labels for Space Content

Tool to list labels on all content in a space.

Get Page Ancestors

Tool to retrieve all ancestors for a given Confluence page by its ID.

Get Page by ID

Tool to retrieve a Confluence page by its ID.

Get Page Footer Comments

Tool to retrieve footer (non-inline) comments for a Confluence page.

Get Page Inline Comments

Tool to retrieve inline comments for a Confluence page.

Get Page Like Count

Tool to get like count for a Confluence page.

Get Pages

Tool to retrieve a paginated list of Confluence pages.

Get Page Versions

Tool to retrieve all versions of a specific Confluence page.

Get Space by ID

Tool to retrieve a Confluence space by its ID.

Get Space Contents

Tool to retrieve content in a Confluence space.

Get Space Properties

Tool to get properties of a Confluence space.

Get Spaces

Tool to retrieve a paginated list of Confluence spaces with optional filtering.

Get Tasks

Tool to list Confluence tasks (action items) with filtering by assignee, creator, space, page, blog post, status, and dates.

Get Anonymous User

Tool to retrieve information about the anonymous user.

Search Content

Searches for content by filtering pages from the Confluence v2 API with intelligent ranking.

Search Users

Searches for users using user-specific queries from the Confluence Query Language (CQL).

Update Blogpost

Tool to update a Confluence blog post's title or content.

Update Blogpost Property

Tool to update a property of a specified blog post.

Update Page Content Property

Tool to update a content property on a Confluence page.

Update Whiteboard Content Property

Tool to update a content property on a whiteboard.

Update Page

Tool to update an existing Confluence page, replacing the entire page content.

Update Space Property

Tool to update a space property.

Update Task

Tool to update a Confluence task status.

FRAMEWORKS

How to build Confluence MCP Agent with another framework

ChatGPT

Use Confluence MCP with ChatGPT

OpenAI Agents SDK

Use Confluence MCP with OpenAI Agents SDK

Claude Agent SDK

Use Confluence MCP with Claude Agent SDK

Claude Code

Use Confluence MCP with Claude Code

Claude Cowork

Use Confluence MCP with Claude Cowork

Codex

Use Confluence MCP with Codex

Cursor

Use Confluence MCP with Cursor

OpenClaw

Use Confluence MCP with OpenClaw

Hermes

Use Confluence MCP with Hermes

CLI

Use Confluence MCP with CLI

Google ADK

Use Confluence MCP with Google ADK

LangChain

Use Confluence MCP with LangChain

Mastra AI

Use Confluence MCP with Mastra AI

LlamaIndex

Use Confluence MCP with LlamaIndex

CrewAI

Use Confluence MCP with CrewAI

OpenCode

Use Confluence MCP with OpenCode

VS Code

Use Confluence MCP with VS Code

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Gmail

Oauth2

Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.

Outlook

Oauth2S2s Oauth2

Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.

Slack

Oauth2

Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place.

Gong

BasicOauth2

Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.

FAQ

Frequently asked questions

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

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

Start with Confluence.It takes 30 seconds.

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

Start building

Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

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 Confluence MCP with Vercel AI SDK v6

Connect Confluence without auth hassles

Introduction

Also integrate Confluence with

TL;DR

What is Vercel AI SDK?

What is the Confluence 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 and Triggers

How to build Confluence MCP Agent with another framework

ChatGPT

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

Cursor

OpenClaw

Hermes

CLI

Google ADK

LangChain

Mastra AI

LlamaIndex

CrewAI

OpenCode

VS Code

Explore Other Toolkits

Gmail

Outlook

Slack

Gong

Frequently asked questions

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

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

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

How safe is my data with Composio Tool Router?+

Start with Confluence.It takes 30 seconds.

Teams ship real agents on Composio