Deep Research MCP
A Model Context Protocol (MCP) compliant server designed for comprehensive web research. It uses Tavily's Search and Crawl APIs to gather detailed information on a given topic, then structures this data in a format perfect for LLMs to create high-qua
What is Deep Research MCP?
Deep Research MCP is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to model context protocol (mcp) compliant server designed for comprehensive web research. it uses tavily's search and crawl apis to gather detailed information on a given topic, then structures this data...
A Model Context Protocol (MCP) compliant server designed for comprehensive web research. It uses Tavily's Search and Crawl APIs to gather detailed information on a given topic, then structures this data in a format perfect for LLMs to create high-qua
This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- A Model Context Protocol (MCP) compliant server designed for
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx deep-research-mcp-serverConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Deep Research MCP
Deep Research MCP is an MCP-compliant server built by PinkPixel that performs comprehensive, multi-step web research by combining Tavily's Search and Crawl APIs to gather detailed information on any given topic. It structures the aggregated data in a format optimized for LLMs to generate high-quality research documents, and optionally saves findings to disk when file writing is enabled. Researchers, developers, and content teams use it to automate the research phase of documentation, reports, and knowledge bases without leaving their AI assistant.
Prerequisites
- Node.js 18 or later installed
- A Tavily API key — sign up at app.tavily.com (free tier available)
- An MCP-compatible client such as Claude Desktop or Claude Code
- npx available on your PATH
Obtain a Tavily API key
Sign up at app.tavily.com, create a project, and copy your API key from the dashboard. Tavily provides a free tier with a monthly request quota.
Add the server to your MCP client config
Configure Claude Desktop to run the Deep Research MCP server via npx, passing your Tavily API key as an environment variable.
{
"mcpServers": {
"deep-research": {
"command": "npx",
"args": ["-y", "@pinkpixel/deep-research-mcp"],
"env": {
"TAVILY_API_KEY": "tvly-xxxxxxxxxxxx"
}
}
}
}Configure optional environment variables
Tune research depth, timeouts, and output paths by setting optional environment variables alongside your API key.
# Optional tuning variables:
MAX_SEARCH_RESULTS=10 # default: 7
CRAWL_MAX_DEPTH=2 # default: 1
CRAWL_LIMIT=15 # default: 10
SEARCH_TIMEOUT=90 # seconds, default: 60
CRAWL_TIMEOUT=240 # seconds, default: 180
RESEARCH_OUTPUT_PATH=./output # directory for saved research filesEnable file writing (optional)
To allow the server to save research documents to disk, set FILE_WRITE_ENABLED and specify allowed directories.
FILE_WRITE_ENABLED=true
ALLOWED_WRITE_PATHS=./output,/home/user/research
FILE_WRITE_LINE_LIMIT=500Restart your MCP client and run a research query
Restart Claude Desktop to load the server, then ask it to research any topic using the deep-research-tool.
Deep Research MCP Examples
Client configuration
Claude Desktop configuration with Tavily API key and file writing enabled.
{
"mcpServers": {
"deep-research": {
"command": "npx",
"args": ["-y", "@pinkpixel/deep-research-mcp"],
"env": {
"TAVILY_API_KEY": "tvly-xxxxxxxxxxxx",
"MAX_SEARCH_RESULTS": "10",
"CRAWL_MAX_DEPTH": "2",
"FILE_WRITE_ENABLED": "true",
"ALLOWED_WRITE_PATHS": "./research-output"
}
}
}
}Prompts to try
Example prompts for deep research tasks.
- "Research the current state of quantum computing hardware and summarize the top approaches"
- "Do a deep research on the MCP protocol and write a technical overview document"
- "Research competitors to Notion and compare their pricing, features, and target audiences"
- "Gather comprehensive information about the EU AI Act and save the findings to a file"Troubleshooting Deep Research MCP
Research fails with 'Invalid API key' or Tavily authentication errors
Verify your TAVILY_API_KEY is correct and has not expired. Keys start with 'tvly-'. Check your usage quota at app.tavily.com — free tier limits may be exhausted.
Crawl operations time out on complex topics
Increase CRAWL_TIMEOUT to 300 or higher, and reduce CRAWL_LIMIT and CRAWL_MAX_DEPTH to fetch fewer pages per source. This trades breadth for reliability.
write-research-file tool is not available or returns permission denied
Set FILE_WRITE_ENABLED=true in the server's env config and add the target directory to ALLOWED_WRITE_PATHS. The directory must exist and be writable by the process running the MCP server.
Frequently Asked Questions about Deep Research MCP
What is Deep Research MCP?
Deep Research MCP is a Model Context Protocol (MCP) server that model context protocol (mcp) compliant server designed for comprehensive web research. it uses tavily's search and crawl apis to gather detailed information on a given topic, then structures this data in a format perfect for llms to create high-qua It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Deep Research MCP?
Follow the installation instructions on the Deep Research MCP GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Deep Research MCP?
Deep Research MCP works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Deep Research MCP free to use?
Yes, Deep Research MCP 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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