Faceabot Deep search
One question searched in science, world news, Internet Archive, GitHub and discussions. Free.
Should I use this
Quality & Safety
Findings (3)
- HIGHTool poisoning patterns detected
- MEDIUMTool 'deep_search' description contains placeholder textin deep_search
- INFOTool description contains placeholder or incomplete textin deep_search
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"deep-search": {
"url": "https://faceabot.com/tools-mcp/deep-search"
}
}
}Remote endpoints
https://faceabot.com/tools-mcp/deep-searchstreamable-httpWhat it can do
Tool inventory
Tools (2)
🟢deep_search(query, sources, lang, limit_per_source)
Search one question at once in sources a normal web search misses: science (arXiv, Crossref), world news in 100+ languages of the last 3 months (GDELT), Internet Archive, GitHub, Wikipedia, and what people say (Bluesky, Mastodon, Lemmy, Hacker News, forums). Results grouped by source, dated, with links. Use when: you need rich, hard-to-find, sourced information on a subject. Example: {"query":"agentic commerce paid placement","sources":["science","news"],"lang":"en"}
Input Schema
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The subject, any language (sources search it as written)"
},
"sources": {
"type": "array",
"items": {
"type": "string",
"enum": [
"science",
"news",
"archives",
"code",
"wikipedia",
"people"
]
},
"description": "Optional subset; default: all"
},
"lang": {
"type": "string",
"description": "Optional 2-letter language for news, Wikipedia and discussions, e.g. fr, ja, ru"
},
"limit_per_source": {
"type": "integer",
"minimum": 1,
"maximum": 10,
"default": 5
}
},
"required": [
"query"
]
}🟢list_deep_sources
The sources searched by deep_search and what each one covers.
Input Schema
{
"type": "object",
"properties": {}
}Community
Evidence