# How to integrate Perplexityai MCP with Claude Code

```json
{
  "title": "How to integrate Perplexityai MCP with Claude Code",
  "toolkit": "Perplexityai",
  "toolkit_slug": "perplexityai",
  "framework": "Claude Code",
  "framework_slug": "claude-code",
  "url": "https://composio.dev/toolkits/perplexityai/framework/claude-code",
  "markdown_url": "https://composio.dev/toolkits/perplexityai/framework/claude-code.md",
  "updated_at": "2026-05-12T10:21:48.578Z"
}
```

## Introduction

Manage your Perplexityai directly from Claude Code with zero worries about OAuth hassles, API-breaking issues, or reliability and security concerns.
You can do this in two different ways:
- Via [Composio Connect](https://dashboard.composio.dev/login?utm_source=toolkits&utm_medium=framework_template&utm_campaign=claude-code&utm_content=composio_connect&next=%2F~%2Forg%2Fconnect%2Fclients%2Fclaude-code) - Direct and easiest approach
- Via [Composio SDK](https://docs.composio.dev/docs?utm_source=toolkits&utm_medium=framework_template&utm_campaign=claude-code&utm_content=composio_sdk) - Programmatic approach with more control

## Also integrate Perplexityai with

- [ChatGPT](https://composio.dev/toolkits/perplexityai/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/perplexityai/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/perplexityai/framework/claude-agents-sdk)
- [Claude Cowork](https://composio.dev/toolkits/perplexityai/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/perplexityai/framework/codex)
- [Cursor](https://composio.dev/toolkits/perplexityai/framework/cursor)
- [VS Code](https://composio.dev/toolkits/perplexityai/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/perplexityai/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/perplexityai/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/perplexityai/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/perplexityai/framework/cli)
- [Google ADK](https://composio.dev/toolkits/perplexityai/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/perplexityai/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/perplexityai/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/perplexityai/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/perplexityai/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/perplexityai/framework/crew-ai)

## TL;DR

- Only one MCP URL to connect multiple apps with Claude Code with zero auth hassles.
- Programmatic tool calling allows LLMs to write its code in a remote workbench to handle complex tool chaining. Reduces to-and-fro with LLMs for frequent tool calling.
- Handling Large tool responses out of LLM context to minimize context rot.
- Dynamic just-in-time access to 20,000 tools across 1000+ other Apps for cross-app workflows. It loads the tools you need, so LLMs aren't overwhelmed by tools you don't need.

## Connect Perplexityai to Claude Code

### Connecting Perplexityai to Claude Code using Composio
1. Add the Composio MCP to Claude

```bash
claude mcp add --scope user --transport http composio https://connect.composio.dev/mcp
```

## What is Claude Code?

Claude Code is Anthropic's command line developer tool that lets you use Claude directly inside your terminal. Instead of switching between your editor, browser, and chat, you can stay in your project folder and ask Claude to help you build, debug, refactor, and understand code right where you're working.
Key features include:
- Terminal-Native Experience: Work with Claude directly in your command line without switching contexts
- MCP Support: Built-in support for Model Context Protocol servers to extend Claude's capabilities
- Project Context: Claude understands your project structure and can read, write, and modify files
- Interactive Development: Ask questions, debug code, and get help in real-time while coding
- Multi-Platform: Works on macOS, Linux, WSL, and Windows

## What is the Perplexityai MCP server, and what's possible with it?

The Perplexityai 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's conversational AI models, so your agent can perform actions like running search queries, generating detailed answers, summarizing content, and retrieving citations automatically.
- Conversational AI search and Q&A: Let your agent ask questions or search a wide range of topics, returning clear, human-like answers from Perplexity's advanced models.
- Contextual and multi-turn queries: Enable your agent to conduct follow-up questions and maintain context for more in-depth, accurate answers.
- Model selection and fine-tuning: Allow your agent to choose between different Perplexity AI models and adjust parameters like temperature, top-k, and top-p for tailored responses.
- Source citations and image retrieval: Have your agent fetch answers with source citations and relevant images, providing richer, more trustworthy outputs.
- Auto-prompting and query refinement: Let your agent automatically enhance and refine user queries for better, more relevant search results.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PERPLEXITYAI_CREATE_ASYNC_CHAT_COMPLETION` | Create Async Chat Completion | Create Async Chat Completion (POST /v1/async/sonar). Submits an asynchronous chat completion request for long-running tasks. Returns immediately with a request ID that can be polled using the Get Async Chat Completion action. Only the 'sonar-deep-research' model is supported for async processing. Async jobs have a 7-day TTL. Deep research generates very long responses (10K-100K+ words) with exhaustive multi-source analysis. Use the idempotency_key to prevent duplicate submissions. Poll with Get Async Chat Completion using the returned request ID to retrieve results when status is COMPLETED. |
| `PERPLEXITYAI_CREATE_CHAT_COMPLETION` | Create Chat Completion | Perplexity Sonar Chat Completions (POST /v1/sonar). Generates web-grounded conversational AI responses with citations. Supports multiple Sonar models optimized for different use cases: - sonar: Fast, cost-effective for simple queries - sonar-pro: Enhanced quality for complex questions - sonar-reasoning-pro: Chain-of-thought reasoning with blocks - sonar-deep-research: Exhaustive multi-source research (generates very long responses, 10K+ words; prefer the async endpoint for this model) Features: web search grounding, citations, images, structured JSON output, search filtering by domain/date/language/recency, and streaming. Important constraints: - search_recency_filter and date filters (search_after_date_filter, search_before_date_filter, etc.) are mutually exclusive. Use one or the other, not both. - Messages with the 'tool' role must alternate with 'assistant' messages. A valid pattern is: system -> user -> assistant -> tool -> user. - The 'stop' parameter is not currently supported by the API. |
| `PERPLEXITYAI_CREATE_CONTEXTUALIZED_EMBEDDINGS` | Create Contextualized Embeddings | Create Contextualized Embeddings (POST /v1/contextualizedembeddings). Generates document-aware embeddings where chunks from the same document share context. Unlike standard embeddings, these recognize sequential relationships within documents, improving retrieval quality. Models: pplx-embed-context-v1-0.6b (1024 dims) and pplx-embed-context-v1-4b (2560 dims). Both support Matryoshka dimension reduction and INT8/binary quantization. |
| `PERPLEXITYAI_CREATE_EMBEDDINGS` | CreateEmbeddings | Generate vector embeddings for independent texts (queries, sentences, documents). This action takes one or more input texts and generates vector embeddings using Perplexity AI's embedding models. Embeddings are useful for semantic search, similarity matching, and machine learning downstream tasks. Supported models: - pplx-embed-v1-0.6b: Smaller, faster model (1024 dimensions) - pplx-embed-v1-4b: Larger, more accurate model (2560 dimensions) The output embeddings are base64-encoded for efficient transmission. Use the dimensions parameter to reduce embedding size for faster processing when full precision is not required (Matryoshka representation). |
| `PERPLEXITYAI_EXECUTE_AGENT` | Execute Agent | Create Agent Response (POST /v1/agent). Orchestrates multi-step agentic workflows with built-in tools (web search, URL fetching, function calling), reasoning, and multi-model support. Streaming is not supported by this action. At least one of 'model', 'models', or 'preset' must be provided. Available presets: 'fast-search', 'pro-search', 'deep-research'. The 'deep-research' preset generates very long responses (10K-100K+ words) with exhaustive multi-source analysis. Available models include Perplexity Sonar, OpenAI, Anthropic, Google, xAI, and NVIDIA models at direct provider rates. Use the List Models action to see available model identifiers. |
| `PERPLEXITYAI_GET_ASYNC_CHAT_COMPLETION` | Get Async Chat Completion | Get Async Chat Completion (GET /v1/async/sonar/{id}). Retrieves the result of an asynchronous chat completion request by its ID. Use this to poll for the result after creating an async job. The response includes the status and, when completed, the full completion. |
| `PERPLEXITYAI_LIST_ASYNC_CHAT_COMPLETIONS` | List Async Chat Completions | List Async Chat Completions (GET /v1/async/sonar). Retrieves a list of all asynchronous chat completion requests for the authenticated user. Use this to see the status of all your pending, completed, and failed async jobs. |
| `PERPLEXITYAI_LIST_MODELS` | List Models | List Models (GET /v1/models). Lists models available for the Agent API. Returns model identifiers that can be used with the Agent endpoint. The response follows the OpenAI List Models format for compatibility. This is a public endpoint that does not require authentication. |
| `PERPLEXITYAI_SEARCH` | Perplexity Search (Raw Results) | Search the Web (POST /search). Returns raw, ranked web search results directly from Perplexity's index without LLM processing. Faster and cheaper than chat completions when you need raw results. Supports filtering by domain, date, language, country, and recency. Max 20 results per request. Important: search_recency_filter and date filters (search_after_date_filter, search_before_date_filter, last_updated_after_filter, last_updated_before_filter) are mutually exclusive. Use one or the other, not both. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Perplexityai MCP server is an implementation of the Model Context Protocol that connects Claude Code (and other AI assistants like Claude and Cursor) directly to your Perplexityai account. It provides structured and secure access so Claude can perform Perplexityai operations on your behalf.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Claude Pro, Max, or API billing enabled Anthropic account
- Composio API Key
- A Perplexityai account
- Basic knowledge of Python or TypeScript

### 1. Install Claude Code

To install Claude Code, use one of the following methods based on your operating system:
```bash
# macOS, Linux, WSL
curl -fsSL https://claude.ai/install.sh | bash

# Windows PowerShell
irm https://claude.ai/install.ps1 | iex

# Windows CMD
curl -fsSL https://claude.ai/install.cmd -o install.cmd && install.cmd && del install.cmd
```

### 2. Set up Claude Code

Open a terminal, go to your project folder, and start Claude Code:
- Claude Code will open in your terminal
- Follow the prompts to sign in with your Anthropic account
- Complete the authentication flow
- Once authenticated, you can start using Claude Code
```bash
cd your-project-folder
claude
```

### 3. Set up environment variables

Create a .env file in your project root with the following variables:
- COMPOSIO_API_KEY authenticates with Composio (get it from [Composio dashboard](https://dashboard.composio.dev/login?utm_source=toolkits&utm_medium=framework_template&utm_campaign=claude-code&utm_content=api_key&next=%2F~%2Forg%2Fconnect%2Fclients%2Fclaude-code))
- USER_ID identifies the user for session management (use any unique identifier)
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
```

### 4. Install Composio library

No description provided.
```python
pip install composio-core python-dotenv
```

```typescript
npm install @composio/core dotenv
```

### 5. Generate Composio MCP URL

No description provided.
```python
import os
from composio import Composio
from dotenv import load_dotenv

load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
USER_ID = os.getenv("USER_ID")

composio_client = Composio(api_key=COMPOSIO_API_KEY)

composio_session = composio_client.create(
    user_id=USER_ID,
    toolkits=["perplexityai"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url

print(f"MCP URL: {COMPOSIO_MCP_URL}")
print(f"\nUse this command to add to Claude Code:")
print(f'claude mcp add --transport http perplexityai-composio "{COMPOSIO_MCP_URL}" --headers "X-API-Key:{COMPOSIO_API_KEY}"')
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';

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 composioClient = new Composio({ apiKey: COMPOSIO_API_KEY });

const composioSession = await composioClient.create(USER_ID, {
  toolkits: ['perplexityai'],
});

const composioMcpUrl = composioSession?.mcp.url;

console.log(`MCP URL: ${composioMcpUrl}`);
console.log(`\nUse this command to add to Claude Code:`);
console.log(`claude mcp add --transport http perplexityai-composio "${composioMcpUrl}" --headers "X-API-Key:${COMPOSIO_API_KEY}"`);
```

### 6. Run the script and copy the MCP URL

No description provided.
```python
python generate_mcp_url.py
```

```typescript
node --loader ts-node/esm generate_mcp_url.ts
# or if using tsx
tsx generate_mcp_url.ts
```

### 7. Add Perplexityai MCP to Claude Code

In your terminal, add the MCP server using the command from the previous step. The command format is:
- claude mcp add registers a new MCP server with Claude Code
- --transport http specifies that this is an HTTP-based MCP server
- The server name (perplexityai-composio) is how you'll reference it
- The URL points to your Composio Tool Router session
- --headers includes your Composio API key for authentication
After running the command, close the current Claude Code session and start a new one for the changes to take effect.
```bash
claude mcp add --transport http perplexityai-composio "YOUR_MCP_URL_HERE" --headers "X-API-Key:YOUR_COMPOSIO_API_KEY"

# Then restart Claude Code
exit
claude
```

### 8. Verify the installation

Check that your Perplexityai MCP server is properly configured.
- This command lists all MCP servers registered with Claude Code
- You should see your perplexityai-composio entry in the list
- This confirms that Claude Code can now access Perplexityai tools
If everything is wired up, you should see your perplexityai-composio entry listed:
```bash
claude mcp list
```

### 9. Authenticate Perplexityai

The first time you try to use Perplexityai tools, you'll be prompted to authenticate.
- Claude Code will detect that you need to authenticate with Perplexityai
- It will show you an authentication link
- Open the link in your browser (or copy/paste it)
- Complete the Perplexityai authorization flow
- Return to the terminal and start using Perplexityai through Claude Code
Once authenticated, you can ask Claude Code to perform Perplexityai operations in natural language. For example:
- "Summarize the latest AI research papers"
- "Generate a creative story about space travel"
- "Explain quantum computing in simple terms"

## Complete Code

```python
import os
from composio import Composio
from dotenv import load_dotenv

load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
USER_ID = os.getenv("USER_ID")

composio_client = Composio(api_key=COMPOSIO_API_KEY)

composio_session = composio_client.create(
    user_id=USER_ID,
    toolkits=["perplexityai"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url

print(f"MCP URL: {COMPOSIO_MCP_URL}")
print(f"\nUse this command to add to Claude Code:")
print(f'claude mcp add --transport http perplexityai-composio "{COMPOSIO_MCP_URL}" --headers "X-API-Key:{COMPOSIO_API_KEY}"')
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';

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 composioClient = new Composio({ apiKey: COMPOSIO_API_KEY });

const composioSession = await composioClient.create(USER_ID, {
  toolkits: ['perplexityai'],
});

const composioMcpUrl = composioSession?.mcp.url;

console.log(`MCP URL: ${composioMcpUrl}`);
console.log(`\nUse this command to add to Claude Code:`);
console.log(`claude mcp add --transport http perplexityai-composio "${composioMcpUrl}" --headers "X-API-Key:${COMPOSIO_API_KEY}"`);
```

## Conclusion

You've successfully integrated Perplexityai with Claude Code using Composio's MCP server. Now you can interact with Perplexityai directly from your terminal using natural language commands.
Key features of this setup:
- Terminal-native experience without switching contexts
- Natural language commands for Perplexityai operations
- Secure authentication through Composio's managed MCP
- Tool Router for dynamic tool discovery and execution
Next steps:
- Try asking Claude Code to perform various Perplexityai operations
- Add more toolkits to your Tool Router session for multi-app workflows
- Integrate this setup into your development workflow for increased productivity
You can extend this by adding more toolkits, implementing custom workflows, or building automation scripts that leverage Claude Code's capabilities.

## How to build Perplexityai MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/perplexityai/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/perplexityai/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/perplexityai/framework/claude-agents-sdk)
- [Claude Cowork](https://composio.dev/toolkits/perplexityai/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/perplexityai/framework/codex)
- [Cursor](https://composio.dev/toolkits/perplexityai/framework/cursor)
- [VS Code](https://composio.dev/toolkits/perplexityai/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/perplexityai/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/perplexityai/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/perplexityai/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/perplexityai/framework/cli)
- [Google ADK](https://composio.dev/toolkits/perplexityai/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/perplexityai/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/perplexityai/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/perplexityai/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/perplexityai/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/perplexityai/framework/crew-ai)

## Related Toolkits

- [Composio](https://composio.dev/toolkits/composio) - 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](https://composio.dev/toolkits/composio_search) - 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](https://composio.dev/toolkits/browser_tool) - 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](https://composio.dev/toolkits/ai_ml_api) - 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.
- [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application.
- [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities.
- [Anthropic administrator](https://composio.dev/toolkits/anthropic_administrator) - Anthropic administrator is an API for managing Anthropic organizational resources like members, workspaces, and API keys. It helps you automate admin tasks and streamline resource management across your Anthropic organization.
- [Api labz](https://composio.dev/toolkits/api_labz) - Api labz is a platform offering a suite of AI-driven APIs and workflow tools. It helps developers automate tasks and build smarter, more efficient applications.
- [Apipie ai](https://composio.dev/toolkits/apipie_ai) - Apipie ai is an AI model aggregator offering a single API for accessing top AI models from multiple providers. It helps developers build cost-efficient, latency-optimized AI solutions without juggling multiple integrations.
- [Astica ai](https://composio.dev/toolkits/astica_ai) - Astica ai provides APIs for computer vision, NLP, and voice synthesis. Integrate advanced AI features into your app with a single API key.
- [Bigml](https://composio.dev/toolkits/bigml) - BigML is a machine learning platform that lets you build, train, and deploy predictive models from your data. Its intuitive interface and robust API make machine learning accessible and efficient.
- [Botbaba](https://composio.dev/toolkits/botbaba) - Botbaba is a platform for building, managing, and deploying conversational AI chatbots across messaging channels. It streamlines chatbot automation, making it easier to integrate AI into customer interactions.
- [Botpress](https://composio.dev/toolkits/botpress) - Botpress is an open-source platform for building, deploying, and managing chatbots. It helps teams automate conversations and deliver rich, interactive messaging experiences.
- [Chatbotkit](https://composio.dev/toolkits/chatbotkit) - Chatbotkit is a platform for building and managing AI-powered chatbots using robust APIs and SDKs. It lets you easily add conversational AI to your apps for better user engagement.
- [Cody](https://composio.dev/toolkits/cody) - Cody is an AI assistant built for businesses, trained on your company's knowledge and data. It delivers instant answers and insights, tailored for your team.
- [Context7 MCP](https://composio.dev/toolkits/context7_mcp) - Context7 MCP delivers live, version-specific code docs and examples right from the source. It helps developers and AI agents instantly retrieve authoritative programming info—no more out-of-date docs.
- [Customgpt](https://composio.dev/toolkits/customgpt) - CustomGPT.ai lets you build and deploy chatbots tailored to your own data and business needs. Get precise and context-aware AI conversations without writing code.
- [Datarobot](https://composio.dev/toolkits/datarobot) - Datarobot is a machine learning platform that automates model development, deployment, and monitoring. It empowers organizations to quickly gain predictive insights from large datasets.
- [Deepgram](https://composio.dev/toolkits/deepgram) - Deepgram is an AI-powered speech recognition platform for accurate audio transcription and understanding. It enables fast, scalable speech-to-text with advanced audio intelligence features.
- [DeepImage](https://composio.dev/toolkits/deepimage) - DeepImage is an AI-powered image enhancer and upscaler. Get higher-quality images with just a few clicks.

## Frequently Asked Questions

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

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.

### Can I use Tool Router MCP with Claude Code?

Yes, you can. Claude Code 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.

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

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.

### 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 Perplexityai data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)