rival-search-mcp
Deterministic deep research via RivalSearchMCP. 9 tools: 5-engine web search (DuckDuckGo/Bing/Yahoo/Mojeek/Wikipedia), 9-platform social search (Reddit/HN/StackOverflow/Dev.to/Medium/ProductHunt/Bluesky/Lobste.rs/Lemmy), 5-source news (Google/Bing/Guardian/GDELT/DDG), 5 academic DBs (OpenAlex/CrossRef/arXiv/PubMed/EuropePMC), GitHub search, website mapping, content extraction with OCR, and research topic synthesis. No API keys required. Use when the user needs web research, competitive analysis, content discovery, or academic paper search.
npx skills add majiayu000/claude-skill-registry --skill rival-search-mcp-damionrashford-rivalsearchmcp-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# RivalSearchMCP You have access to 9 research tools via the CLI at `scripts/cli.py`. Run all commands with `uv run scripts/cli.py`. Every tool returns deterministic, auditable output. There is no in-server LLM — you're the one doing the synthesis. ## How to invoke tools ```bash uv run scripts/cli.py call-tool <tool_name> --flag value ``` ## Available tools - `web_search` — concurrent search across DuckDuckGo, Bing, Yahoo, Mojeek, Wikipedia. Use for general web queries. - `social_search` — Reddit, Hacker News, Stack Overflow, Dev.to, Medium, Product Hunt, Bluesky, Lobste.rs, Lemmy. Use for community discussions. - `news_aggregation` — Google News, Bing News, The Guardian, GDELT, DuckDuckGo News. Use for current events. Accepts `--time-range day|week|month|anytime`. - `github_search` — search public GitHub repos. Use for code, libraries, projects. - `map_website` — crawl a site in `research` / `docs` / `map` mode. Use to explore site structure or documentation. - `content_operations` — one tool, six ops (`retrieve`, `stream`, `analyze`, `extract`, `score`, `find_conflicts`). Use to get full page content, rate source quality, or surface disagreements between sources. - `document_anal
- How to invoke tools
- Available tools
- When to chain tools
- Tool reference
- Output
uv run scripts/cli.py call-tool <tool_name> --flag value
What does the rival-search-mcp skill do?
Deterministic deep research via RivalSearchMCP. 9 tools: 5-engine web search (DuckDuckGo/Bing/Yahoo/Mojeek/Wikipedia), 9-platform social search (Reddit/HN/StackOverflow/Dev.to/Medium/ProductHunt/Bluesky/Lobste.rs/Lemmy), 5-source news (Google/Bing/Guardian/GDELT/DDG), 5 academic DBs (OpenAlex/CrossRef/arXiv/PubMed/EuropePMC), GitHub search, website mapping, content extraction with OCR, and research topic synthesis. No API keys required. Use when the user needs web research, competitive analysis, content discovery, or academic paper search.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill rival-search-mcp-damionrashford-rivalsearchmcp-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.