Best MCP servers for research
Research with an AI agent is fundamentally about defeating the training cutoff: a base model is frozen in time, so it cannot tell you what happened last week or cite a source it has actually read. A research MCP setup grounds the model in live data through three steps: search to find sources, fetch to read full pages, and a documentation lookup when the question is about a specific library or API. The servers below cover that loop, from grounded conversational answers with citations to neural search and clean page extraction. Combine a search server with a fetch server for the best results; add a docs server when research touches code. Each ships a verified, current install config.
Perplexity
Perplexity
Perplexity's official Sonar MCP server: give your agent live web search, conversational answers, deep research, and reasoning.
Perplexity's official Sonar server gives the agent grounded conversational answers, deep research, and reasoning that cite live sources rather than relying on stale training data.
Exa
Exa
Exa's official server gives agents neural web search and clean full-page content built for LLMs.
Exa's neural search is tuned for AI rather than humans and returns clean full-page content, so the agent reads real sources instead of a list of links.
Firecrawl
Firecrawl
Official Firecrawl server that turns any website into clean, LLM-ready data through scrape, crawl, map, search, and extract.
Firecrawl turns any source page into clean, model-ready markdown and can crawl a whole site, the fetch-and-read step that follows discovery.
Context7
Upstash
Pulls version-accurate library docs and code examples into your agent's context on demand.
When research touches code, Context7 pulls version-accurate library docs and examples into context so findings about an API reflect the current version.