MCP 服务器

deep-search

Free, open-source search engine MCP server with 7 sources, 29 tools, and semantic search via ChromaDB at zero cost.

README

Deep Search Engine MCP Server

Free, Open-Source Search Engine MCP Server — 7 sources, 10 consolidated tools, semantic search via ChromaDB, zero cost.

Features

7 Data Sources: Web, Reddit, YouTube, GitHub, Twitter/X, DuckDuckGo, Wikipedia
10 Consolidated Tools: All features preserved, combined by mode/action parameters
Semantic Search: ChromaDB + sentence-transformers (all-MiniLM-L6-v2)
100% Free: No API keys, no subscriptions, no paid APIs
MCP Standard: Works with Claude, Cursor, OpenCode, and other AI clients
Parallel Crawling: asyncio-based concurrent data collection

Installation

Option 1: Plugin Installation (Recommended)

OpenCode:

{
  "plugin": ["deep-search@git+https://github.com/sukirman1901/DeepSearch.git"]
}

Claude Code: Add to .mcp.json or ~/.claude/config.json:

{
  "mcpServers": {
    "deep-search": {
      "command": "python3",
      "args": ["server.py"],
      "cwd": "/path/to/DeepSearch/mcp"
    }
  }
}

Option 2: Manual Installation

# Clone the repository
git clone https://github.com/sukirman1901/DeepSearch.git
cd DeepSearch

# Create virtual environment
python3.12 -m venv .venv
source .venv/bin/activate

# Install dependencies
pip install -r mcp/requirements.txt

Available Tools (10)

`search` — Unified Search (7 modes)

Mode	Description	Key Params
`basic` (default)	Semantic search across indexed content	source, limit, category, search_depth, topic, max_age_hours
`advanced`	Search with domain/date/text/source filters	include_domains, exclude_domains, start_date, end_date
`quick`	Real-time search without database (DuckDuckGo)	source
`stream`	Search with streaming batches + timing	sources
`smart`	Compact IR overview + full details (saves 50-70% tokens)	top_full, max_overview_tokens
`code`	Search GitHub + Stack Overflow for code snippets	language, tokens_target
`context`	Token-budget-aware snippet packing	budget_tokens, language

`crawl` — Crawl & Extract

Mode	Description	Key Params
Single URL	Crawl URL + subpages, index results	url, subpages, subpage_target
Batch	Extract content from multiple URLs	urls, extract_depth, instructions

`monitor` — Persistent Monitoring

Action	Description
`create`	Create a monitor for a query
`list`	List all monitors
`run`	Run monitor, returns only NEW results
`delete`	Delete a monitor

`webset` — Entity Collection

Action	Description
`create`	Create a named container
`add`	Search and add results
`list`	List all websets
`get`	Get webset with all items
`enrich`	Scrape for emails, social links, tech
`delete`	Delete a webset

`info` — Engine Information

Type	Description
`categories`	List all search categories
`sources`	List all 7 data sources
`stats`	Database + cache statistics
`detect`	Auto-detect category for a query

`research` — Deep Research Sessions

Action	Description
`start`	Start a research session
`followup`	Ask follow-up question
`list`	List all sessions
`delete`	Delete a session

Other Tools

Tool	Description
`answer`	Search + synthesis with inline citations
`search_leads`	Lead generation with ICP scoring
`site_map`	BFS website structure mapping
`index_topic`	Crawl and index a topic

Architecture

DeepSearch/
├── mcp/                    # MCP server implementation
│   ├── crawlers/           # 7 specialized crawlers + subpage discovery
│   ├── db/                # ChromaDB + sentence-transformers
│   ├── search/            # Engine, answer, context, streaming, research, monitors, websets, sitemap, extract
│   ├── tests/             # 192 tests
│   ├── server.py          # 10 consolidated MCP tools
│   └── requirements.txt
├── skills/                # AI skills
│   └── using-deep-search/SKILL.md
├── hooks/                 # Session hooks
├── docs/superpowers/specs/ # Design specs
└── README.md