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Rival Search Plugin

A Claude Code plugin with AI research agent skills powered by MCP.

No API keys, no subscriptions, no configuration. Install and start researching.

Powered by RivalSearchMCP — 10 MCP research tools across web, social, news, GitHub, academic, and document sources.


What This Claude Code Plugin Does

This Claude Code plugin gives Claude a complete AI research platform — 10 MCP tools, 5 agent skills, and 6 specialist agents that work together to handle any research task.

  • 10 MCP tools via RivalSearchMCP — web search, social media, news, GitHub, academic papers, document analysis, and more
  • 5 agent skills — slash commands that run multi-step research workflows and produce structured reports
  • 6 AI research agents — specialist analysts that Claude invokes automatically based on your task
  • Portable hooks — audit logging and quality gates that travel with the plugin

Example Queries

Once this Claude Code plugin is installed, try these agent skills:

"Research the current state of AI code generation tools"
/rival-search:competitive-intel Cursor
/rival-search:fact-check "OpenAI revenue exceeded $2 billion in 2024"
/rival-search:due-diligence Anthropic
/rival-search:trend-intel AI agents for software development

Getting Started

Claude Code Marketplace (Recommended)

/plugin marketplace add damionrashford/rival-search
/plugin install rival-search@damionrashford-rival-search

Local Directory

git clone https://github.com/damionrashford/rival-search.git
claude --plugin-dir ./rival-search

This Claude Code plugin auto-connects to the hosted RivalSearchMCP MCP server. All 10 tools work immediately — no setup, no API keys.


MCP Research Tools

All 10 MCP tools are provided by RivalSearchMCP — zero authentication required.

Tool What It Does
web_search Multi-engine search across DuckDuckGo, Yahoo, and Wikipedia
social_search Search Reddit, Hacker News, Dev.to, Product Hunt, Medium
news_aggregation Aggregate news from Google News, DuckDuckGo News, Yahoo News
github_search Search GitHub repositories with rate limiting
map_website Intelligent website exploration and mapping
content_operations Retrieve, analyze, and extract content from any URL
document_analysis Extract text from PDFs, Word docs, and images with OCR
scientific_research Academic papers (arXiv, Semantic Scholar) and datasets (Kaggle, HuggingFace)
research_topic End-to-end research workflow for quick topic analysis
research_agent AI agent with autonomous multi-tool research

Agent Skills

This Claude Code plugin includes 5 agent skills — slash commands that orchestrate MCP tools into multi-step research workflows with structured reports and citations.

Agent Skill Description
/rival-search:research <topic> Comprehensive research with academic depth — papers, datasets, implementations
/rival-search:competitive-intel <company or market> Company, product, market, or website intelligence with SWOT analysis
/rival-search:due-diligence <company or person> Full due diligence with risk assessment — works for companies and individuals
/rival-search:trend-intel <topic> News digest + trend trajectory with velocity indicators and maturity assessment
/rival-search:fact-check <claim> Cross-source claim verification with confidence scoring and evidence chains

AI Research Agents

This Claude Code plugin includes 6 AI research agents. Each agent has a defined methodology, quality gates, and preloaded agent skills.

Agent Specialty
research-analyst Lead researcher — deep multi-source investigation
competitive-intel SWOT analysis, competitor profiling, market positioning
fact-checker Cross-source claim verification, confidence scoring
trend-analyst Trend identification, velocity tracking, trajectory projection
content-strategist Content gap analysis, audience research, brief creation
due-diligence Company/person investigation, risk assessment, red/green flags

How This Claude Code Plugin Works

  1. .mcp.json — Connects to RivalSearchMCP via MCP at https://RivalSearchMCP.fastmcp.app/mcp. All 10 MCP tools available automatically.

  2. skills/ — Five agent skill files with step-by-step research workflows, exact MCP tool parameters, and structured output formats.

  3. agents/ — Six AI research agents with full Claude Code frontmatter (tools, agent skills, hooks, memory). Invoked automatically or manually.

  4. hooks/hooks.json — Portable event hooks for audit logging and output quality validation.


Structure

rival-search-plugin/
├── .claude-plugin/
│   ├── plugin.json            # Claude Code plugin manifest
│   └── marketplace.json       # Marketplace config
├── .mcp.json                  # MCP server → RivalSearchMCP.fastmcp.app/mcp
├── agents/
│   ├── research-analyst.md
│   ├── competitive-intel.md
│   ├── fact-checker.md
│   ├── trend-analyst.md
│   ├── content-strategist.md
│   └── due-diligence.md
├── skills/
│   ├── research/
│   ├── competitive-intel/
│   ├── due-diligence/
│   ├── trend-intel/
│   └── fact-check/
├── hooks/
│   └── hooks.json
├── CLAUDE.md
├── LICENSE
└── README.md

FAQ

Does this Claude Code plugin require payment?

No. MIT licensed, powered by RivalSearchMCP. No API keys, no subscriptions, no hidden costs.

Do I need API keys?

No. Install and go. This Claude Code plugin auto-connects to the hosted RivalSearchMCP MCP server.

What's the difference between agent skills and agents?

Agent skills are slash commands you invoke explicitly (/rival-search:research <topic>). Agents are invoked automatically by Claude when your task matches their expertise.

Can I use MCP tools directly without agent skills?

Yes. Agent skills are guided workflows, but you can ask Claude to use any RivalSearchMCP MCP tool directly.


Contributing

Contributions welcome — new agent skills, AI research agent improvements, or bug fixes.

  1. Fork the project
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

Issues & Feedback

Open an Issue

Links

License

MIT — see LICENSE for details.

Releases

No releases published

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