Perplexity Server

The Perplexity MCP Server bridges Claude and Perplexity’s web‑search API, giving AI assistants instant access to up‑to‑date information without leaving the conversation. By exposing a dedicated search tool, the server lets Claude fetch fresh data, citations, and authoritative sources directly from the web. This capability is essential for developers building knowledge‑intensive applications, such as research assistants, customer support bots, or data‑driven recommendation engines that require real‑time facts.

At its core, the server performs intelligent query routing: it analyses the user’s request and automatically selects the most suitable Perplexity model—ranging from quick “sonar” queries to deep‑research or reasoning‑focused variants. Developers can override this default with a environment variable, but the auto‑selection logic ensures optimal performance for each intent. The result is a smooth workflow where Claude can ask the server to “search the web” and receive a concise, well‑structured answer that includes source links and model metadata.

Key capabilities include:

• Model‑aware search: Automatic switching among , , , , and based on query intent.
• Domain filtering: Fine‑grained control over allowed or blocked domains, allowing teams to enforce compliance or focus on trusted sources.
• Citation transparency: Every response contains the source URLs and a note indicating which model was used, enabling users to verify facts or audit the assistant’s behavior.
• CLI‑style control: Commands such as give developers natural language hooks for configuration without leaving the chat.

Real‑world scenarios that benefit from this server include:

• Academic research assistants: Students can request “deep research on quantum computing” and receive comprehensive, citation‑rich summaries.
• Enterprise knowledge bases: Support agents can pull the latest policy documents or product updates from internal portals by filtering domains to company sites.
• News aggregation: Media bots can quickly retrieve the latest headlines, with the system choosing a lightweight model for speed or a deeper one for context‑rich analysis.

Integration into AI workflows is straightforward: once the server is registered in Claude’s configuration, the assistant automatically recognizes the “search” tool and can invoke it on demand. The server’s intelligent model selection and domain controls give developers fine‑grained authority over the assistant’s browsing behavior, ensuring that the tool aligns with organizational policies while still delivering up‑to‑date information.