Deep Research Server
БесплатноНе проверенAn MCP server for deep research that performs search, scraping, synthesis, fact-checking, and persistent memory, enabling users to conduct comprehensive researc
Описание
An MCP server for deep research that performs search, scraping, synthesis, fact-checking, and persistent memory, enabling users to conduct comprehensive research tasks via Claude.
README
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, fetch |
Orchestrated deep research |
| Returns raw HTML | Cheerio + Turndown → clean markdown + headings, links, meta |
| No memory | Persistent memory in ~/.mcp-deep-research/ |
| One page at a time | Parallel 3-worker scraper, 10min cache |
| No reasoning | Fact-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)
| Tool | What it does | Params |
|---|---|---|
search_web |
DuckDuckGo HTML search, no API key, UDDG decode | query, count 1-10, timeFilter |
scrape_page |
Fetch + main-content heuristic + markdown | `url, format=markdown |
extract_insights |
Entities, stats regex, key-point scoring, reading time | content, goal? |
deep_research |
Power tool — search → parallel scrape → synthesize report | `topic, depth=quick |
compare_sources |
2-5 URLs → consensus vs unique vs contradictions | urls[], focus? |
fact_check_claim |
Searches support + debunked OR false, heuristic verdict |
claim, searchDepth |
memory_save |
Save finding to JSON, survives restarts | key, value, tags[], source? |
memory_search |
Fuzzy search in persistent memory | query, tags[], limit |
Resources:
research://memory— all saved findingsresearch://history— last 100 actionsresearch://stats— cache size, uptime
Prompts:
deep-dive-research— full research workflowfact-check— fact-checker squadcompare-narratives— bias & comparison table
Install
git clone https://github.com/SECRET4422/mcp-deep-research-server.git
cd mcp-deep-research-server
npm install
npm run build
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 findingshistory.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.jsonfor 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)
- Blocklist for SSRF (169.254.169.254 etc)
- Smithery registry
Dev
npm run dev # tsx watch
npm run build
npm run lint
Guidelines in CONTRIBUTING.md.
License
MIT © SECRET4422 — See LICENSE
Built with 🧠 for Dehradun → World. Not a generic MCP.
Установка Deep Research Server
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/SECRET4422/mcp-deep-research-serverFAQ
Deep Research Server MCP бесплатный?
Да, Deep Research Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Deep Research Server?
Нет, Deep Research Server работает без API-ключей и переменных окружения.
Deep Research Server — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Deep Research Server в Claude Desktop, Claude Code или Cursor?
Открой Deep Research Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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