Mcp Omnisearch

Mcp Omnisearch is a unified Model Context Protocol (MCP) server that aggregates the search and AI‑generation capabilities of several leading providers—Tavily, Perplexity, Kagi, Jina AI, Brave, Exa AI, and Firecrawl—into a single, developer‑friendly interface. By exposing these diverse services under one MCP contract, the server eliminates the need to maintain separate API keys, SDKs, or query formats for each provider. Developers can therefore compose richer AI workflows that seamlessly switch between factual search, code discovery, and real‑time answer generation without changing the underlying client logic.

The server’s core value lies in its search‑operator abstraction. Brave and Kagi support a rich set of native operators (site, filetype, language, date ranges, exact phrases, etc.) that can be embedded directly in the query string. Tavily and Exa provide domain filtering via API parameters, while GitHub search offers advanced code‑search syntax (filename, path, repo, user, language). This uniform operator model lets developers craft highly targeted queries—such as “filetype:pdf lang:en site:microsoft.com +typescript -javascript”—and receive consistent, structured results regardless of the underlying provider. The ability to combine multiple operators in a single request gives fine‑grained control over search scope and relevance, which is especially valuable for compliance or data‑quality pipelines.

Beyond raw search, Mcp Omnisearch bundles AI response tools that blend up‑to‑date web data with powerful language models. Perplexity AI delivers real‑time answers that merge GPT‑4 Omni and Claude 3 outputs, while Kagi FastGPT offers lightning‑fast citations with sub‑second latency. Exa Answer provides neural search–powered responses that surface concise, contextually relevant information. These tools can be invoked directly from the MCP client, allowing developers to ask complex questions and receive citations or code snippets without leaving the chat interface.

Typical use cases include research assistants, where a user can query academic papers, legal documents, or industry reports across multiple engines and obtain a consolidated answer with citations. Developer tooling benefits from GitHub code search combined with AI explanations, enabling rapid onboarding or automated documentation generation. Compliance and data‑quality workflows can leverage domain filtering to restrict searches to trusted sources, while the unified operator syntax ensures consistent logging and auditability.

In summary, Mcp Omnisearch offers a single entry point for diverse search providers and AI generation tools, unified operator support, and fast, citation‑rich responses. It streamlines the integration of external knowledge into AI assistants, reduces operational overhead, and empowers developers to build sophisticated, data‑driven applications with minimal friction.