Content & SEO research
Mine what people actually ask and say — Reddit, Hacker News, Stack Overflow, news, and the live web — to ground content in real demand, not guesswork.
social_searchweb_searchnews_aggregation
what agents do with it
One server, every research job.
RivalSearchMCP turns an AI agent into a research analyst — pulling web, social, news, academic, code, and document signals into one auditable answer.
// 01
Competitor & market analysis
Profile any company across news, social chatter, GitHub activity, and the open web in one fan-out. Spot positioning, launches, and sentiment shifts — then reconcile conflicting figures with find_conflicts.
research_topic · entitynews_aggregationsocial_search
// 02
Academic & deep research
Search five paper providers and four dataset hubs at once, citation-scored and relevance-ranked. From literature review to dataset discovery without leaving the agent.
scientific_researchcontent_operations
// 03
Due diligence
Build a defensible profile of a person, startup, or product — cross-checking claims across independent sources and surfacing where they disagree, instead of trusting one black-box answer.
research_topic · entitycontent_operations · score
// 04
// 05
Developer research
Find libraries, read docs, and compare repos. github_search ranks by stars; map_website in docs mode turns any documentation site into clean, structured context.
github_searchmap_website · docs
// 06
Fact-checking & verification
Score sources on tier, freshness, and corroboration, then detect numeric, date, and polarity disagreements across 2–10 sources — so the agent flags conflicts instead of averaging them away.
content_operations · scorefind_conflicts
Point your agent at all 28 sources.
Free, open source, zero API keys. One URL and your agent is a research analyst.