Search · MODEL CONTEXT PROTOCOL
reading plus ai mcp server deep research
reading plus ai mcp server deep research is a community-listed Model Context Protocol server. Review the source repository before installation.
WHAT IT CONNECTS
What reading plus ai mcp server deep research gives an AI Agent
- **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
- **deep-research**: Tailored for comprehensive research tasks with a structured approach
- macOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`
- Windows: `%APPDATA%/Claude/claude_desktop_config.json`
- **Sync Dependencies**
- **Build Distributions**
- **Publish to PyPI**
SECURITY
An MCP listing is not a security review
An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.
README
Repository documentation
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.
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
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
- deep-research: Tailored for comprehensive research tasks with a structured approach
- macOS:
~/Library/Application\ Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%/Claude/claude_desktop_config.json
"mcpServers": {
"mcp-server-deep-research": {
"command": "uv",
"args": [
"--directory",
"/Users/username/repos/mcp-server-application/mcp-server-deep-research",
"run",
"mcp-server-deep-research"
]
}
}"mcpServers": {
"mcp-server-deep-research": {
"command": "uvx",
"args": [
"mcp-server-deep-research"
]
}
}-
Sync Dependencies
uv sync
-
Build Distributions
uv build
Generates source and wheel distributions in the dist/ directory.
-
Publish to PyPI
uv publish
Contributions are welcome! Whether you're fixing bugs, adding features, or improving documentation, your help makes this project better.
This project is licensed under the MIT License. See the LICENSE file for details.
COMMUNITY