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How to integrate Perplexityai MCP with Claude Agent SDK

Connect Claude Agent SDK 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 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

Introduction

This guide walks you through connecting Perplexityai to the Claude Agent SDK 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 Claude Agent SDK 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.

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TL;DR

Here's what you'll learn:
  • Get and set up your Claude/Anthropic and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Perplexityai
  • Configure an AI agent that can use Perplexityai as a tool
  • Run a live chat session where you can ask the agent to perform Perplexityai operations

What is Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework for building AI agents powered by Claude. It provides a streamlined interface for creating agents with MCP tool support and conversation management.

Key features include:

  • Native MCP Support: Built-in support for Model Context Protocol servers
  • Permission Modes: Control tool execution permissions
  • Streaming Responses: Real-time response streaming for interactive applications
  • Context Manager: Clean async context management for sessions

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:

  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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Composio API Key and Claude/Anthropic API Key
  • Primary know-how of Claude Agents SDK
  • A Perplexityai account
  • Some knowledge of Python
2

Getting API Keys for Claude/Anthropic and Composio

Claude/Anthropic API Key
  • Go to the Anthropic Console and create an API key. You'll need credits to use the models.
  • 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 @anthropic-ai/claude-agent-sdk @composio/core dotenv

Install the Composio SDK and the Claude Agents SDK.

What's happening:

  • @composio/core provides Composio integration for Anthropic
  • @anthropic-ai/claude-agent-sdk is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID identifies the user for session management
  • ANTHROPIC_API_KEY authenticates with Anthropic/Claude
5

Import dependencies

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

dotenv.config();
What's happening:
  • We're importing all necessary libraries including the Claude Agent SDK and Composio
  • The dotenv.config() function loads environment variables from your .env file
  • This setup prepares the foundation for connecting Claude with Perplexityai functionality
6

Create a Composio instance and Tool Router session

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });

  // Create Tool Router session for Perplexityai
  const session = await composio.create(USER_ID, {
    toolkits: ['perplexityai'],
  });
  const mcpUrl = session?.mcp.url;
What's happening:
  • The function checks for the required COMPOSIO_API_KEY environment variable
  • We're creating a Composio instance using our API key
  • The create method creates a Tool Router session for Perplexityai
  • The returned url is the MCP server URL that your agent will use
7

Configure Claude Agent with MCP

const options: Options = {
  permissionMode: 'bypassPermissions',
  mcpServers: {
    composio: {
      type: 'http',
      url: mcpUrl,
      headers: { 'x-api-key': COMPOSIO_API_KEY }
    }
  },
  systemPrompt: 'You are a helpful assistant with access to Perplexityai tools via Composio.',
  maxTurns: 10,
};
What's happening:
  • We're configuring the Claude Agent options with the MCP server URL
  • permissionMode: 'bypassPermissions' allows the agent to execute operations without asking for permission each time
  • The system prompt instructs the agent that it has access to Perplexityai
  • maxTurns: 10 limits the conversation length to prevent excessive API usage
8

Create client and start chat loop

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

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}
What's happening:
  • The readline interface is created to handle user input and output
  • The query function is used to send the user's input to the agent
  • The chat loop continues until the user types 'exit' or 'quit'
9

Run the application

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}
What's happening:
  • The chat function is the entry point for the application
  • The try-catch block is used to handle any errors that occur

Complete Code

Here's the complete code to get you started with Perplexityai and Claude Agent SDK:

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });
  const session = await composio.create(USER_ID, {
    toolkits: ['perplexityai']
  });
  const mcp_url = session?.mcp.url;

  const options: Options = {
    permissionMode: 'bypassPermissions',
    mcpServers: {
      composio: {
        type: 'http',
        url: mcp_url,
        headers: { 'x-api-key': COMPOSIO_API_KEY }
      }
    },
    systemPrompt: 'You are a helpful assistant with access to Perplexityai tools via Composio.',
    maxTurns: 10,
  };

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

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}

Conclusion

You've successfully built a Claude Agent SDK agent that can interact with Perplexityai through Composio's Tool Router.

Key features:

  • Native MCP support through Claude's agent framework
  • Streaming responses for real-time interaction
  • Permission bypass for smooth automated workflows
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
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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FAQ

Frequently asked questions

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