MCP Deep Research Server

Community Search and web

Autonomous multi-source deep research with DuckDuckGo search (zero API keys), parallel scrapers, markdown cleaning, synthesis with citations, fact-checking, and persistent memory.

What can you do with MCP Deep Research Server?

  • ✅ Logo + pro README + badges
  • ✅ GitHub Actions CI (Node 18/20/22) + Release workflow
  • ✅ Issue templates, PR template, CONTRIBUTING, SECURITY
  • ✅ .editorconfig, smoke test script
  • ✅ Optimized package.json for npm publishing
  • ✅ CHANGELOG tracked

Install

The installation steps are in the documentation below. Documentation

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Deep Research MCP Server

Non-generic MCP for real research. Search → Scrape → Synthesize → Fact-check → Remember.


Why not generic?
Generic MCP (boring)This MCP (pro)
echo, fetchOrchestrated deep research
Returns raw HTMLCheerio + Turndown → clean markdown + headings, links, meta
No memoryPersistent memory in ~/.mcp-deep-research/
One page at a timeParallel 3-worker scraper, 10min cache
No reasoningFact-check with stance scoring, contradiction detection
Architecture
graph LR
    A[User: deep_research topic] --> B[search_web DDG HTML]
    B --> C[Parallel Scrape x3-8]
    C --> D[cheerio clean + turndown md]
    D --> E[extract_insights heuristic]
    E --> F[Synthesize Report + Citations]
    F --> G[memory_save + history]
    F --> H[Return to Claude]
    
    I[compare_sources] --> C
    J[fact_check_claim] --> B
    K[memory_search] --> G
Tools (8)
ToolWhat it doesParams
search_webDuckDuckGo HTML search, no API key, UDDG decodequery, count 1-10, timeFilter
scrape_pageFetch + main-content heuristic + markdown`url, format=markdowntextfull, extractMainOnly`
extract_insightsEntities, stats regex, key-point scoring, reading timecontent, goal?
deep_researchPower tool — search → parallel scrape → synthesize report`topic, depth=quickstandarddeep, maxSources, saveMemory`
compare_sources2-5 URLs → consensus vs unique vs contradictionsurls[], focus?
fact_check_claimSearches support + debunked OR false, heuristic verdictclaim, searchDepth
memory_saveSave finding to JSON, survives restartskey, value, tags[], source?
memory_searchFuzzy search in persistent memoryquery, tags[], limit

Resources:

  • research://memory — all saved findings
  • research://history — last 100 actions
  • research://stats — cache size, uptime

Prompts:

  • deep-dive-research — full research workflow
  • fact-check — fact-checker squad
  • compare-narratives — bias & comparison table
Quickstart & Installation

Run this single command in your terminal:

npx mcp-deep-research-server --install

That's it! It automatically detects your OS, writes the config to your claude_desktop_config.json, and configures the 8 research tools. Just restart Claude Desktop.


📦 Install via Smithery

To automatically install for Claude Desktop or Cursor via Smithery:

npx -y @smithery/cli install mcp-deep-research-server --client claude

🛠️ Manual / Other Clients Setup

Run via npx:

npx mcp-deep-research-server

Or build from source:

git clone https://github.com/SECRET4422/mcp-deep-research-server.git
cd mcp-deep-research-server
npm install
npm run build

🤖 Agent Skill (Claude Code / Antigravity / Cursor / Agent Frameworks)

This repository includes an open-standard Agent Skill that teaches AI coding assistants when and how to autonomously run deep research workflows.

  • Import via skill directory: skills/deep-research/
  • Spec compliant with Claude Code, Cursor, and Google Antigravity agents.
Test (smoke)
npm run test:mcp
# or
npm run inspect # opens http://localhost:6274

Manually tested:

[search] Dehradun → 3 results ✓
[deep_research] What is MCP → 3 sources in 2.1s ✓
tools/list → 8 tools ✓
Add to Claude Desktop

Edit config:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "deep-research": {
      "command": "node",
      "args": ["/absolute/path/to/mcp-deep-research-server/build/index.js"]
    }
  }
}

Restart Claude Desktop.

Add to Cursor / Windsurf / VS Code

.cursor/mcp.json or mcp.json:

{
  "mcpServers": {
    "deep-research": {
      "command": "node",
      "args": ["./build/index.js"],
      "cwd": "/path/to/mcp-deep-research-server"
    }
  }
}
Example Prompts

Deep Research:

Use deep_research to research "Best LLM fine-tuning in 2026, depth deep" then compare LoRA vs QLoRA

Fact Check:

Fact check claim: "Bun is faster than Node" using fact_check_claim

Compare:

Compare these 3 URLs about MCP architecture focusing on security: https://modelcontextprotocol.io/docs/getting-started/intro https://www.anthropic.com/news/model-context-protocol https://en.wikipedia.org/wiki/Model_Context_Protocol

See examples/claude-example.md for more.

Data Storage

All in ~/.mcp-deep-research/:

  • memory.json — persistent findings
  • history.json — audit log (100 max)
  • cache/ — reserved

No DB, no external calls except search/scrape.

Pro Features in v1.1.0
  • ✅ Logo + pro README + badges
  • ✅ GitHub Actions CI (Node 18/20/22) + Release workflow
  • ✅ Issue templates, PR template, CONTRIBUTING, SECURITY
  • ✅ .editorconfig, smoke test script
  • ✅ Optimized package.json for npm publishing
  • ✅ CHANGELOG tracked
Roadmap
  • [ ] Tavily / Brave API fallback if keys present
  • [ ] PDF parsing via pdf-parse
  • [ ] YouTube transcript tool
  • [ ] Vector search on memory (embeddings)
  • [x] SSRF protection — private/internal IP blocklist for scrape_page
  • [x] Smithery & Glama registry integration
Dev
npm run dev     # tsx watch
npm run build
npm run lint

Guidelines in CONTRIBUTING.md.

License

MIT © Prabhakar Pal — See LICENSE

Built with 🧠 for Dehradun → World. Not a generic MCP.

Frequently asked questions

What is MCP Deep Research Server?

Autonomous multi-source deep research with DuckDuckGo search (zero API keys), parallel scrapers, markdown cleaning, synthesis with citations, fact-checking, and persistent memory.

How do I install MCP Deep Research Server?

Follow the installation steps in its documentation, shown on this page and in its repository.

Is MCP Deep Research Server open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains MCP Deep Research Server?

It is published by SECRET4422. AI.tn lists it but does not maintain or endorse it.

From the community awesome-mcp-servers lists and the project's GitHub repository. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.