How to integrate Confluence MCP with Mastra AI

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Introduction

This guide walks you through connecting Confluence to Mastra AI 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, create a private space for product roadmap drafts through natural language commands.

This guide will help you understand how to give your Mastra AI 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.

TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Confluence tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Confluence tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Confluence agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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.

Supported Tools & Triggers

Tools
Add Content LabelTool to add labels to a piece of content.
Get Space by IDTool to retrieve a confluence space by its id.
Create BlogpostTool to create a new confluence blog post.
Create Blogpost PropertyTool to create a property on a specified blog post.
Create Whiteboard PropertyTool to create a new content property on a whiteboard.
Create PageTool to create a new confluence page in a specified space.
Create Page PropertyTool to create a property on a confluence page.
Create Private SpaceTool to create a private confluence space.
Create SpaceTool to create a new confluence space.
Create Space PropertyTool to create a new property on a confluence space.
Create WhiteboardTool to create a new confluence whiteboard.
Delete Blogpost PropertyTool to delete a blog post property.
Delete Page Content PropertyTool to delete a content property from a page by property id.
Delete Whiteboard Content PropertyTool to delete a content property from a whiteboard by property id.
Delete PageTool to delete a confluence page.
Delete SpaceTool to delete a confluence space by its key.
Delete Space PropertyTool to delete a space property.
Get Attachment LabelsTool to list labels on an attachment.
Get AttachmentsTool to retrieve attachments of a confluence page.
Get Audit LogsTool to retrieve confluence audit records.
Get Blogpost by IDTool to retrieve a specific confluence blog post by its id.
Get Blogpost LabelsTool to retrieve labels of a specific confluence blog post by id.
Get Blogpost Like CountTool to get like count for a confluence blog post.
Get Blogpost OperationsTool to retrieve permitted operations for a confluence blog post.
Get BlogpostsTool to retrieve a list of blog posts.
Get Blog PostsTool to retrieve a list of blog posts.
Get Blog Posts For LabelTool to list all blog posts under a specific label.
Get Blogpost Version DetailsTool to retrieve details for a specific version of a blog post.
Get Blogpost VersionsTool to retrieve all versions of a specific blog post.
Get Child PagesTool to list all direct child pages of a given confluence page.
Get Blog Post Content PropertiesTool to retrieve all content properties on a blog post.
Get Page Content PropertiesTool to retrieve all content properties on a page.
Get Content RestrictionsTool to retrieve restrictions on a confluence content item.
Get Current UserTool to get information about the currently authenticated user.
Get Inline Comments for Blog PostTool to retrieve inline comments for a confluence blog post.
Get LabelsTool to retrieve all labels in a confluence site.
Get Page LabelsTool to retrieve labels of a specific confluence page by id.
Get Labels for SpaceTool to list labels on a space.
Get Labels for Space ContentTool to list labels on all content in a space.
Get Page AncestorsTool to retrieve all ancestors for a given confluence page by its id.
Get Page by IDTool to retrieve a confluence page by its id.
Get Page Like CountTool to get like count for a confluence page.
Get PagesTool to retrieve a list of pages.
Get Page VersionsTool to retrieve all versions of a specific confluence page.
Get Space by IDTool to retrieve a confluence space by its id.
Get Space ContentsTool to retrieve content in a confluence space.
Get Space PropertiesTool to get properties of a confluence space.
Get SpacesTool to retrieve a list of confluence spaces.
Get Anonymous UserTool to retrieve information about the anonymous user.
Search ContentSearches for content by filtering pages from the confluence v2 api with intelligent ranking.
Search UsersSearches for users using user-specific queries from the confluence query language (cql).
Update BlogpostTool to update a confluence blog post's title or content.
Update Blogpost PropertyTool to update a property of a specified blog post.
Update Page Content PropertyTool to update a content property on a confluence page.
Update Whiteboard Content PropertyTool to update a content property on a whiteboard.
Update PageTool to update an existing confluence page.
Update Space PropertyTool to update a space property.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Confluence through MCP.

Install dependencies

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

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

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

if (!openaiAPIKey) 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 as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session

Create a Tool Router session for Confluence

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["confluence"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Confluence MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "confluence" for Confluence access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Confluence toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "confluence-mastra-agent",
    instructions: "You are an AI agent with Confluence tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\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({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        confluence: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

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

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Confluence toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Confluence and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

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

if (!openaiAPIKey) 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 as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["confluence"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      confluence: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "confluence-mastra-agent",
    instructions: "You are an AI agent with Confluence tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

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

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { confluence: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Confluence through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows

How to build Confluence MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Confluence MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Confluence MCP with Claude Agent SDK

Google ADK

Google ADK

Use Confluence MCP with Google ADK

LangChain

LangChain

Use Confluence MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Confluence MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Confluence MCP with LlamaIndex

CrewAI

CrewAI

Use Confluence MCP with CrewAI

FAQ

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

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.

Can I use Tool Router MCP with Mastra AI?

Yes, you can. Mastra AI 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.

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

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.

How safe is my data with Composio Tool Router?

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.

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