Deep Research & Competitor Analysis MCP for Claude & Cursor. No API Keys. Features: Web Search, Social Media (Reddit/HN), Trends & OCR.
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RivalSearchMCP is an MCP server that deep Research & Competitor Analysis MCP for Claude & Cursor. No API Keys. Features: Web Search, Social Media (Reddit/HN), Trends & OCR. Its tool list has not been published yet over stdio and http, requires no API key, and scores 73/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"RivalSearchMCP": {
"url": "https://RivalSearchMCP.fastmcp.app/mcp"
}
}
}Are you the author?
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Advanced MCP server for web research, content discovery, social media analysis, and AI-powered research.
No automated test available for this server. Check the GitHub README for setup instructions.
Five weighted categories - click any category to see the underlying evidence.
No known CVEs.
No package registry to scan.
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Deterministic research MCP server — web + social + academic + news + code + docs, all in one place. No API keys, no in-server LLM, structured outputs for agent chaining.
🆓 100% Free & Open Source — No API keys or subscriptions for core tools. The hosted server includes fair-use rate limiting.
RivalSearchMCP is a FastMCP 3.x server exposing 9 specialized tools that search, fetch, score, and compare information across:
No LLM runs inside the server. Every tool returns deterministic, auditable output — the caller's model does the synthesis. Tools that benefit from structured output (content_operations score, find_conflicts) return ToolResult with both a human-readable markdown rendering and a parseable structuredContent dict, so agents can chain tool outputs without regex-parsing prose.
content_operations find_conflicts surfaces numeric, date, and polarity disagreements across sources as a first-class signal instead of averaging them awayresearch_topic(mode="entity") fans out to 8 sources in parallel and returns a unified report with confidenceOnce connected, try asking your AI assistant:
"Use RivalSearchMCP to research FastAPI vs Django. Run
research_topicon both, aggregate recent news, check Reddit and Hacker News discussions, search GitHub for activity, look for academic papers, score the top sources, and flag any conflicts between them."
RivalSearchMCP runs as a remote MCP server hosted on FastMCP. Just follow the steps below to install, and go.
[](https://cursor.com/en-US/install-mcp?name=RivalSearchMCP&config=eyJ1cmwiOiJodHRwczovL1JpdmFsU2V