RivalSearch
Deterministic research MCP server on FastMCP 3 — 5-engine web search, 9-platform social search, 6 academic DBs, news aggregation, entity profiles, conflict detection, document analysis. No API keys. No in-server LLM. Structured outputs for agent chai
What is RivalSearch?
RivalSearch is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to deterministic research mcp server on fastmcp 3 — 5-engine web search, 9-platform social search, 6 academic dbs, news aggregation, entity profiles, conflict detection, document analysis. no api keys. n...
Deterministic research MCP server on FastMCP 3 — 5-engine web search, 9-platform social search, 6 academic DBs, news aggregation, entity profiles, conflict detection, document analysis. No API keys. No in-server LLM. Structured outputs for agent chai
This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Deterministic research MCP server on FastMCP 3 — 5-engine we
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx rivalsearchmcpConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use RivalSearch
RivalSearchMCP is a deterministic, no-API-key research MCP server built on FastMCP 3 that gives AI agents access to nine research tools covering five web search engines, nine social platforms, six academic databases, news aggregation, entity profiling, conflict detection, document analysis, and GitHub search. Every tool returns structured, quality-scored outputs designed for agent chaining — making it suitable for competitive intelligence, academic research, and multi-source fact verification workflows. Because it runs no in-server LLM and requires no API keys, it is free to use and produces reproducible results.
Prerequisites
- An MCP client such as Claude Desktop, Cursor, or Claude Code
- For the hosted server: no additional software required
- For local installation: Python 3.10+ and the FastMCP library
- Git (if installing locally)
Use the hosted server (easiest option)
The fastest way to get started is to point your MCP client at the hosted RivalSearchMCP server. No local installation, no API keys, no configuration beyond one URL.
claude mcp add RivalSearchMCP --url https://RivalSearchMCP.fastmcp.app/mcpOr configure the hosted URL manually
Add the hosted server to your claude_desktop_config.json or equivalent MCP client config file using the URL transport.
{
"mcpServers": {
"RivalSearchMCP": {
"url": "https://RivalSearchMCP.fastmcp.app/mcp"
}
}
}Or clone and run locally
For a local installation, clone the repository and use FastMCP to install it into Claude Desktop.
git clone https://github.com/damionrashford/RivalSearchMCP.git
cd RivalSearchMCP
fastmcp install claude-desktop server.pyRun the local server in STDIO or HTTP mode
If using the local installation directly, start the server in STDIO mode for Claude Desktop or HTTP mode for remote clients.
# STDIO mode (for Claude Desktop)
fastmcp run server.py
# HTTP mode (for remote clients)
fastmcp run server.py --transport http --port 8000Verify available tools
Ask your AI client to list the tools provided by RivalSearchMCP. You should see nine tools: web_search, social_search, news_aggregation, github_search, map_website, content_operations, research_topic, document_analysis, and scientific_research.
RivalSearch Examples
Client configuration
claude_desktop_config.json using the hosted RivalSearchMCP server — no API key or local setup required.
{
"mcpServers": {
"RivalSearchMCP": {
"url": "https://RivalSearchMCP.fastmcp.app/mcp"
}
}
}Prompts to try
Example prompts for research, competitive analysis, and multi-source fact verification using RivalSearchMCP's nine tools.
- "Use RivalSearchMCP to research FastAPI vs Django: search Reddit and Hacker News, aggregate recent news, check GitHub activity, look for academic papers, and flag any conflicting claims"
- "Search for entity information about OpenAI and compile a profile with sources from web, news, and social platforms"
- "Find recent academic papers on transformer architecture efficiency and score the top sources"
- "Analyze the content at https://example.com and extract the main claims with quality scores"
- "Search for discussions about Rust vs Go on Reddit, Stack Overflow, and Hacker News and summarize the consensus"Troubleshooting RivalSearch
The hosted URL returns connection errors
Confirm your MCP client supports URL-based transports. Claude Desktop and Claude Code both support the 'url' key in mcpServers. If using an older client that requires STDIO, use the local installation path with 'fastmcp run server.py'.
Web search results are empty or very sparse
RivalSearchMCP uses DuckDuckGo, Bing, Yahoo, Mojeek, and Wikipedia without API keys, so results depend on public search availability. Try more specific queries or use the research_topic tool which orchestrates multiple engines simultaneously for better coverage.
Local installation fails with FastMCP import errors
Install FastMCP with 'pip install fastmcp' before running the server. Confirm you are using Python 3.10+ by running 'python --version'. If dependency conflicts arise, create a fresh virtual environment with 'python -m venv venv && source venv/bin/activate'.
Frequently Asked Questions about RivalSearch
What is RivalSearch?
RivalSearch is a Model Context Protocol (MCP) server that deterministic research mcp server on fastmcp 3 — 5-engine web search, 9-platform social search, 6 academic dbs, news aggregation, entity profiles, conflict detection, document analysis. no api keys. no in-server llm. structured outputs for agent chai It connects AI assistants to external tools and data sources through a standardized interface.
How do I install RivalSearch?
Follow the installation instructions on the RivalSearch GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with RivalSearch?
RivalSearch works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is RivalSearch free to use?
Yes, RivalSearch is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.
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