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How to integrate Perplexityai MCP with LangChain

Connect LangChain to Perplexityai MCP. Summarize the latest ai research papers, generate a creative story about space travel, and more using natural language, with authentication handled for you.

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Perplexityai

Api Key

Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.

28 Tools

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Introduction

This guide walks you through connecting Perplexityai to LangChain using the Composio tool router. By the end, you'll have a working Perplexityai agent that can run chat completions, search the web, create embeddings, execute agents, and check your usage analytics through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Perplexityai account through Composio's Perplexityai 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 Perplexityai with

TL;DR

Here's what you'll learn:

Get and set up your OpenAI and Composio API keys
Connect your Perplexityai project to Composio
Create a Tool Router MCP session for Perplexityai
Initialize an MCP client and retrieve Perplexityai tools
Build a LangChain agent that can interact with Perplexityai
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 Perplexityai MCP server, and what's possible with it?

The Perplexity AI MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Perplexity AI account. It provides structured and secure access to Perplexity AI's conversational models, web search, embeddings, and agent execution, so your agent can search the web, generate responses, run Perplexity agents, create embeddings, and manage asynchronous chat requests on your behalf.

Web search: Have your agent search the web and return relevant results for research, fact-finding, or current topics.
Conversational responses: Let the agent use Perplexity Sonar models to answer questions, explain topics, and generate human-like text.
Asynchronous chat tasks: Direct your agent to start longer chat requests, check their progress, and review previously submitted requests.
Perplexity agent execution: Instruct your agent to run a Perplexity agent for tasks that need an agent-generated response.
Text embeddings and model discovery: Have your agent create standard or contextualized embeddings for text and view the Perplexity models available to your account.

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 step10 STEPS

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

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 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

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

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 Perplexityai functionality through MCP

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 Perplexityai tools
Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

const url = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Perplexityai 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 Perplexityai tools as needed

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "perplexityai-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 Perplexityai MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available Perplexityai tools that the agent can use
We're creating a LangChain agent using the GPT-5 model

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 Perplexityai 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

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 Perplexityai 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: ['perplexityai']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "perplexityai-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 Perplexityai 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 Perplexityai 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

Supported Tools

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

Cancel Agent Response

Request cancellation of an existing durable agent response.

Create Async Chat Completion

Create Async Chat Completion (POST /v1/async/sonar).

Create Chat Completion

Generate a chat-compatible response from conversation messages, with optional search controls.

Create Contextualized Embeddings

Create Contextualized Embeddings (POST /v1/contextualizedembeddings).

CreateEmbeddings

Generate vector embeddings for independent texts (queries, sentences, documents).

Create Orchestrator Chat Completion

Create a non-streaming OpenAI-compatible chat completion using a cataloged Orchestrator model.

Create Orchestrator Message

Create a non-streaming Anthropic-compatible message using an Orchestrator catalog model.

CreateOrchestratorResponse

Generate a non-streaming model response through the Perplexity Orchestrator using a creator/model-name catalog ID, input text or structured items, optional tools, and structured output settings.

Create Skill

Create a Project-owned skill from a ZIP bundle containing SKILL.

Delete Skill

Delete a skill only if its current revision matches expected_revision.

Download Agent Response File

Download a file delivered by an Agent response's share_file tool.

Evaluate Decisions

Evaluate named yes/no, choice, and score questions against shared content.

Execute Agent

Create Agent Response (POST /v1/agent).

Get Agent Response

Retrieve a stored Agent response as a JSON snapshot (GET /v1/agent/{id}).

Get Async Chat Completion

Get Async Chat Completion (GET /v1/async/sonar/{id}).

Get Member Usage Analytics

Get organization Perplexity usage per member in daily UTC buckets.

Get Orchestrator Model

Retrieve one Orchestrator model by its full provider/model id.

Get Skill

Get a skill's metadata by identifier, optionally at a specific revision.

Get Skill Download URL

Get a short-lived URL to download a skill bundle as a ZIP, optionally for a specific revision; omit the revision to select the active revision.

Get Usage Analytics

Get an organization's Perplexity Computer usage as a bucketed time series.

List Agent Response Files

List files an agent response delivered from its sandbox using share_file.

List Async Chat Completions

List a page of legacy asynchronous Sonar chat completion requests for the authenticated user, including their statuses.

List Models

List Models (GET /v1/models).

List Orchestrator Models

List available Orchestrator API models sorted by id, with base token prices.

List Skill Revisions

List a skill's revisions, newest first.

List Skills

List skills in the authenticated Project, newest first.

Perplexity Search (Raw Results)

Search the Web (POST /search).

Update Skill

Upload a new ZIP bundle as a revision of an existing Project-owned skill.

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MORE TOOLKITS

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Toolkit marketplace

Composio

No Auth

Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.

Composio search

No Auth

Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.

Browser tool

No Auth

Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow.

Ai ml api

Api Key

Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows.

FAQ

Frequently asked questions

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

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

Start with Perplexityai.It takes 30 seconds.

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

Start building

How to integrate Perplexityai MCP with LangChain

Connect Perplexityai without auth hassles

Introduction

Also integrate Perplexityai with

TL;DR

What is LangChain?

What is the Perplexityai 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 dependencies

Set up environment variables

Import dependencies

Initialize Composio client

Create a Tool Router session

Configure the agent with the MCP URL

Set up interactive chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Perplexityai MCP Agent with another framework

Claude Code

Cursor

ChatGPT

Claude Cowork

Antigravity

OpenAI Agents SDK

Claude Agent SDK

Grok Bot

Muse

Codex

Kimi Code

Grok Build

VS Code

OpenCode

OpenClaw

Hermes

Atomic Agent

CLI

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Pydantic AI

AutoGen

Explore Other Toolkits

Composio

Composio search

Browser tool

Ai ml api

Frequently asked questions

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

Can I use Tool Router MCP with LangChain?

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

How safe is my data with Composio Tool Router?

Start with Perplexityai.It takes 30 seconds.