Perplexity AI MCP Server
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- FlicenseBqualityDmaintenanceEnables interaction with Perplexity AI through MCP tools for chatting, searching, and retrieving documentation.51-
- AlicenseNot gradedqualityDmaintenanceProvides a standardized interface for interacting with Perplexity's tools and services through a unified API, following the MCP specification.1MIT
- AlicenseNot gradedqualityDmaintenanceA comprehensive MCP server that provides intelligent access to Perplexity AI's search and reasoning models with automatic model selection, conversation management, and project-aware storage. Supports real-time search, deep research, chat sessions, and async operations for complex queries.16 npm3MIT
- AlicenseBqualityAmaintenanceEnables AI agents and users to query Perplexity AI's premium models (GPT-5.4, Claude 4.6 Opus, Gemini 3.1 Pro, etc.) via MCP tools, CLI, or API, with support for deep research, model council, and multi-turn conversations.30145 PyPI187MIT
- AlicenseNot gradedqualityCmaintenanceExposes Perplexity AI's search and synthesis capabilities through MCP, enabling Claude Desktop and other MCP clients to search the web, synthesize sources, and get cited answers.MIT
- AlicenseAqualityDmaintenanceEnables AI assistants to perform web searches and retrieve real-time information using Perplexity AI's Sonar models, with support for multiple search modes and easy integration with MCP clients.51MIT
TDQS
Scored across 5 tools
Most tools have distinct purposes: chat_perplexity handles conversational AI, check_deprecated_code analyzes code deprecation, find_apis discovers APIs, get_documentation retrieves docs, and search performs general queries. However, get_documentation and search could overlap slightly when users seek technical information, but descriptions clarify their focus.
Naming is mixed: chat_perplexity uses a verb_noun format, while check_deprecated_code, find_apis, get_documentation, and search use verb-based phrases without a consistent pattern. All names are snake_case, providing some readability, but the verb styles vary (e.g., 'chat' vs. 'check' vs. 'find'), lacking a unified convention.
With 5 tools, the count is reasonable for a server focused on AI assistance and information retrieval. It covers key areas like conversation, code analysis, API discovery, documentation, and general search, though it might feel slightly thin for broader AI tasks, but each tool earns its place.
The server targets AI-driven information and code assistance, with tools for chat, code checks, API finding, documentation, and search. Notable gaps include lack of update/delete operations for chats or saved searches, and no tool for summarizing or analyzing search results, which could limit agent workflows in this domain.