# Perplexity AI — MCP server on mcp.ai
> Connect your Perplexity AI account and use 9 tools for artificial intelligence straight from your AI agent. Connect with your own API key. Perplexity AI provides conversational AI models for generating human-like text responses.

By: mcp.ai · official
Page: https://mcp.ai/perplexityai

## Connect (MCP protocol)
Remote MCP endpoint (HTTP, streamable): https://api.mcp.ai/p_perplexityai?ms=1787293560000
Add it as a custom/remote MCP connector, then authenticate when prompted.

## REST API (no MCP client required)
Every tool is also a REST endpoint, authed with a workspace API key.
Discover: GET https://api.mcp.ai/api/perplexityai/_endpoints   # public; lists every endpoint
Call:     POST https://api.mcp.ai/api/perplexityai/<endpoint>
  Authorization: Bearer sk_live_…   # create one at https://mcp.ai/settings/api-keys
  Content-Type: application/json
  Body: { …args }   →   { "ok": true, "tool": "<id>", "result": { … } }

## Developer docs
How to use (MCP or REST), markdown: https://mcp.ai/perplexityai/skill.md
Postman collection (v2.1): https://mcp.ai/perplexityai/postman.json

## Tools
- perplexityai_create_async_chat_completion(request: object, idempotency_key?: string) — 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 Asyn
- perplexityai_create_chat_completion(stop?: string|string[], model?: string, top_p?: number, stream?: boolean, messages: object[], max_tokens?: integer, search_mode?: string, stream_mode?: string, temperature?: number, return_images?: boolean, disable_search?: boolean, response_format?: object, reasoning_effort?: string, web_search_options?: object, image_domain_filter?: string[], image_format_filter?: string[], language_preference?: string, search_domain_filter?: string[], search_recency_filter?: string, search_language_filter?: string[], enable_search_classifier?: boolean, return_related_questions?: boolean, search_after_date_filter?: string, last_updated_after_filter?: string, search_before_date_filter?: string, last_updated_before_filter?: string) — 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, 
- perplexityai_create_contextualized_embeddings(input: string[][], model: string, dimensions?: integer, encoding_format?: string) — Create Contextualized Embeddings (POST /v1/contextualizedembeddings). Generates document-aware embeddings where chunks from the same document share context. Unlike standard embeddings, these recognize
- perplexityai_create_embeddings(input: string|string[], model: string, dimensions?: integer, encoding_format?: string) — 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. Embe
- perplexityai_execute_agent(input: string, model?: string, tools?: object[], models?: string[], preset?: string, max_steps?: integer, reasoning?: object, instructions?: string, response_format?: object, max_output_tokens?: integer, language_preference?: string) — 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
- perplexityai_get_async_chat_completion(request_id: string) — 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 respon
- perplexityai_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, 
- perplexityai_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 compa
- perplexityai_search(query: string|string[], country?: string, max_tokens?: integer, max_results?: integer, max_tokens_per_page?: integer, search_domain_filter?: string[], search_recency_filter?: string, search_language_filter?: string[], search_after_date_filter?: string, last_updated_after_filter?: string, search_before_date_filter?: string, last_updated_before_filter?: string) — 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. Suppo

## Example prompts
- "What can I do in Perplexity AI?"
- "Show me a summary of my Perplexity AI account"

## Links
Docs: https://mcp.ai/docs/mcps/perplexityai
Website: https://mcp.ai/mcps/perplexityai