RivalSearchMCP is a comprehensive remote MCP server written in Python that provides 10 web research and analysis tools. Once running, you can connect using any MCP client (e.g., Claude Desktop, Cursor, VS Code, Claude Code) and start leveraging the 10 tools across three main categories: Search & Discovery, Content Analysis, and Research & Scientific. Tools like web_search, social_search, news_aggregation, github_search, map_website help you gather and organize data from multiple sources. Content_analysis tools such as content_operations, research_topic, and document_analysis enable you to extract and analyze content from URLs, documents, and images. The AI-powered research_agent can autonomously orchestrate tool calls to produce structured reports. To begin, run the server locally or connect to the provided FastMCP-hosted remote endpoint, then issue queries or workflows through your MCP client to perform multi-engine searches, social media monitoring, document analysis, and topic research, all without requiring API keys. The server is designed to work without authentication and can be used to streamline end-to-end research workflows with progress tracking across the 10 integrated tools.

Prerequisites:

• Python 3.9+ installed on your system
• Access to a shell/terminal

Option A — Run locally (no extra tooling):

1. Clone the repository git clone https://github.com/damionrashford/RivalSearchMCP.git
2. Navigate into the project cd RivalSearchMCP
3. Run the MCP server directly python server.py

Option B — Install using UV and FastMCP CLI (recommended for MCP clients):

1. Install UV (Python package manager) curl -LsSf https://astral.sh/uv/install.sh | sh
2. Install FastMCP CLI uv tool install fastmcp
3. Start the server with FastMCP (example, running locally):

   Ensure you are in the RivalSearchMCP directory or point to server.py

   fastmcp run server.py

Option C — One-command install (via clone and install for clients):

1. Clone the repository git clone https://github.com/damionrashford/RivalSearchMCP.git
2. Move into the directory cd RivalSearchMCP
3. Install to a client (examples): fastmcp install claude-desktop server.py # Claude Desktop fastmcp install cursor server.py # Cursor fastmcp install claude-code server.py # Claude Code

Notes:

• The server runs as a Python application (server.py) and exposes 10 tools across three capability areas. No API keys are required for the built-in tools, aligning with the project’s no-auth philosophy.
• If you plan to deploy remotely (e.g., FastMCP hosted), refer to the hosted endpoint mentioned in the README and update your MCP client configuration accordingly.
• When running locally, ensure your environment has network access to external sources, as many tools fetch data from the web, social platforms, and repositories.
• If you encounter port or connection issues, verify that the server.py process is running and that the MCP client is configured to reach the correct host/port (default assumptions are local host unless otherwise specified).
• You can customize behavior via client-side configurations; the server itself is designed to be compatible with standard MCP clients such as Claude Desktop, Cursor, VS Code, and Claude Code.