What is reading plus ai mcp server deep research
MCP Server for Deep Research
MCP Server for Deep Research is a tool designed for conducting comprehensive research on complex topics. It helps you explore questions in depth, find relevant sources, and generate structured research reports.
Your personal Research Assistant, turning research questions into comprehensive, well-cited reports.
🚀 Try it Out
*
Youtube: https://youtu.be/_a7sfo5yxoI
-
Download Claude Desktop
- Get it here
-
Install and Set Up
- On macOS, run the following command in your terminal:
python setup.py
-
Start Researching
- Select the deep-research prompt template from MCP
- Begin your research by providing a research question
Features
The Deep Research MCP Server offers a complete research workflow:
-
Question Elaboration
- Expands and clarifies your research question
- Identifies key terms and concepts
- Defines scope and parameters
-
Subquestion Generation
- Creates focused subquestions that address different aspects
- Ensures comprehensive coverage of the main topic
- Provides structure for systematic research
-
Web Search Integration
- Uses Claude's built-in web search capabilities
- Performs targeted searches for each subquestion
- Identifies relevant and authoritative sources
- Collects diverse perspectives on the topic
-
Content Analysis
- Evaluates information quality and relevance
- Synthesizes findings from multiple sources
- Provides proper citations for all sources
-
Report Generation
- Creates well-structured, comprehensive reports as artifacts
- Properly cites all sources used
- Presents a balanced view with evidence-based conclusions
- Uses appropriate formatting for clarity and readability
📦 Components
Prompts
- deep-research: Tailored for comprehensive research tasks with a structured approach
⚙️ Modifying the Server
Claude Desktop Configurations
- macOS:
~/Library/Application\ Support/Claude/claude_desktop_config.json
- Windows:
%APPDATA%/Claude/claude_desktop_config.json
Development (Unpublished Servers)
"mcpServers": {
"mcp-server-deep-research": {
"command": "uv",
"args": [
"--directory",
"`/Users/username/repos/mcp-server-application/mcp-server-deep-research",`
"run",
"mcp-server-deep-research"
]
}
}
Published Servers
"mcpServers": {
"mcp-server-deep-research": {
"command": "uvx",
"args": [
"mcp-server-deep-research"
]
}
}
🛠️ Development
Building and Publishing
-
Sync Dependencies
uv sync
-
Build Distributions
uv build
Generates source and wheel distributions in the dist/ directory.
-
Publish to PyPI
uv publish
🤝 Contributing
Contributions are welcome! Whether you're fixing bugs, adding features, or improving documentation, your help makes this project better.
📜 License
This project is licensed under the MIT License. See the LICENSE file for details.
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Frequently Asked Questions
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
What are MCP Servers?
MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
How do MCP Servers work?
MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.
Are MCP Servers secure?
Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.
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