MCP Server for Deep Research

Provides an MCP server that elaborates questions, generates subquestions, conducts web searches, analyzes content, and produces comprehensive research reports with citations.

python

207

GitHub Stars

python

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "reading-plus-ai-mcp-server-deep-research": {
      "command": "uv",
      "args": [
        "--directory",
        "/Users/username/repos/mcp-server-application/mcp-server-deep-research",
        "run",
        "mcp-server-deep-research"
      ]
    }
  }
}

MCP Server for Deep Research provides an end-to-end workflow for turning complex research questions into structured, well-cited reports. It guides you from question clarification through subquestioning, sourcing information, analyzing quality, and delivering a final artifact that presents evidence-based conclusions.

How to use

You interact with the MCP client to launch the Deep Research server and work through a guided research workflow. Start by selecting the deep-research MCP server and connect it to your MCP client. You will proceed through a sequence of steps: elaborate your core question, generate focused subquestions, run targeted web searches, analyze found sources for quality and relevance, and assemble a comprehensive report that cites each source.

How to install

Prerequisites: ensure you have a compatible MCP client installed. Install the MCP server tooling used by this package in your environment as described below.

Additional sections

Configuration and runtime details are provided below. If you need to modify how the server runs locally, you can start a development instance or a published instance depending on your setup. No external dependencies beyond what is shown here are required for basic use.

Note on development and publishing: you can sync dependencies, build distributions, and publish packages using the MCP tooling. Use the standard commands provided by the MCP workflow to keep your server up to date.

Troubleshooting tips: verify that the MCP server process starts correctly under your MCP client, ensure directory paths used by local runs exist, and confirm that the server logs provide actionable details if a step in the research workflow fails.

Available tools

deep_research

Tailored prompt for comprehensive research tasks with a structured approach.

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