How to integrate Confluence MCP with LangChain

This guide walks you through connecting Confluence to LangChain 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 LangChain 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 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

Introduction

This guide walks you through connecting Confluence to LangChain 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 LangChain 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

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Confluence project to Composio
  • Create a Tool Router MCP session for Confluence
  • Initialize an MCP client and retrieve Confluence tools
  • Build a LangChain agent that can interact with Confluence
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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:

  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 step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming
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 dependencies

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Confluence functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Confluence tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['confluence']
    }
);

const url = 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 session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Confluence tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "confluence-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Confluence MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Confluence tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Confluence related question or task to the agent.\n");

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

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;
    }

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

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

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

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['confluence']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "confluence-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Confluence related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    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;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

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

Conclusion

You've successfully built a LangChain agent that can interact with Confluence through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding 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 logo

ChatGPT

Use Confluence MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Confluence MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Confluence MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Confluence MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Confluence MCP with Claude Cowork

Codex logo

Codex

Use Confluence MCP with Codex

Cursor logo

Cursor

Use Confluence MCP with Cursor

OpenClaw logo

OpenClaw

Use Confluence MCP with OpenClaw

Hermes logo

Hermes

Use Confluence MCP with Hermes

CLI logo

CLI

Use Confluence MCP with CLI

Google ADK logo

Google ADK

Use Confluence MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Confluence MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Confluence MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Confluence MCP with LlamaIndex

CrewAI logo

CrewAI

Use Confluence MCP with CrewAI

OpenCode logo

OpenCode

Use Confluence MCP with OpenCode

VS Code logo

VS Code

Use Confluence MCP with VS Code

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. LangChain 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.

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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.

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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.

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Co-Founder, Ingram Technologies