# Damionrashford Rivalsearchmcp Rivalsearchmcp

> RivalSearchMCP

- Skill: `tomevault-io/damionrashford-rivalsearchmcp-rivalsearchmcp` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/damionrashford-rivalsearchmcp-rivalsearchmcp`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/damionrashford-rivalsearchmcp-rivalsearchmcp/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/damionrashford-rivalsearchmcp-rivalsearchmcp

---


# 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_analysis` — extract text from PDFs, Word docs, images (image OCR via EasyOCR). Use for document processing.
- `research_topic` — end-to-end research workflow for a topic, combining search, content retrieval, and analysis.
- `scientific_research` — OpenAlex, CrossRef, arXiv, PubMed, Europe PMC (papers) + Kaggle, HuggingFace, Dataverse, Zenodo (datasets).

## When to chain tools

- Found a URL from search? → `content_operations --operation retrieve --url <url>`
- Want to assess source trust before using results? → `content_operations --operation score --urls '[…]'`
- Two sources seem to disagree? → `content_operations --operation find_conflicts --urls '[…]'`
- Found a PDF link? → `document_analysis --url <url>`
- Need to explore a website? → `map_website --url <url> --mode docs`
- Need a unified entity profile in one shot? → `research_topic --mode entity --topic "OpenAI"`

## Tool reference

For full flags, types, and defaults for each tool, read:

- [resources/search.md](resources/search.md) — web_search, social_search, news_aggregation, github_search, map_website
- [resources/content.md](resources/content.md) — content_operations, document_analysis
- [resources/research.md](resources/research.md) — research_topic, scientific_research

## Output

All tools return structured text to stdout. Errors go to stderr. Exit codes: 0 success, 1 tool error, 2 connection failed.

---
> Source: [damionrashford/RivalSearchMCP](https://github.com/damionrashford/RivalSearchMCP) — distributed by [TomeVault](https://tomevault.io).
<!-- tomevault:4.0:skill_md:2026-06-19 -->