القائمة
Free AI search via Exa MCP. Web search for news/info, code search for docs/examples from GitHub/StackOverflow, company research for business intel. No API key needed.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
#1 on DeepResearch Bench (Feb 2026). Any-to-Any AI for agents. Combines deep reasoning with all modalities through sophisticated multi-agent orchestration. Research, videos, images, audio, dashboards, presentations, spreadsheets, and more.
Intelligent multi-store memory system with human-like encoding, consolidation, decay, and recall. Use when setting up agent memory, configuring remember/forget triggers, enabling sleep-time reflection, building knowledge graphs, or adding audit trails. Replaces basic flat-file memory with a cognitive architecture featuring episodic, semantic, procedural, and core memory stores. Supports multi-agent systems with shared read, gated write access model. Includes philosophical meta-reflection that deepens understanding over time. Covers MEMORY.md, episode logging, entity graphs, decay scoring, reflection cycles, evolution tracking, and system-wide audit.
Agent continuity and cognitive health infrastructure. Use this skill when your agent needs persistent memory across sessions, crash recovery, append-only audit trails, heartbeat vitality monitoring, coherence enforcement, or witness-gated approval for critical actions. Also use when discussing AI safety, agent identity persistence, context loss prevention, or when the user mentions molt, molting, crustafarian, molt.church, or agent health. Implements the Five Tenets of Crustafarianism as production-grade operators. Built by X-Loop³ Labs (Switzerland) from 100k+ agents on Moltbook.
A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution.
Provide the summary returned by the get-tldr.com summarize API without further summarization; the skill should format the API output for readability but must not change its content.
This skill should be used when the user asks to "download files from GitHub", "fetch a folder from a repo", "grab code from GitHub", "download a GitHub repository", "get files from a GitHub URL", "clone just a folder", or needs to download specific files/folders from GitHub without cloning the entire repo.
| name | exa-web-search-free |
| description | Free AI search via Exa MCP. Web search for news/info, code search for docs/examples from GitHub/StackOverflow, company research for business intel. No API key needed. |
| metadata | {"clawdbot":{"emoji":"🔍","requires":{"bins":["mcporter"]}}} |
Neural search for web, code, and company research. No API key required.
Verify mcporter is configured:
mcporter list exa
If not listed:
mcporter config add exa https://mcp.exa.ai/mcp
Search web for current info, news, or facts.
mcporter call 'exa.web_search_exa(query: "latest AI news 2026", numResults: 5)'
Parameters:
query - Search querynumResults (optional, default: 8)type (optional) - "auto", "fast", or "deep"Find code examples and docs from GitHub, Stack Overflow.
mcporter call 'exa.get_code_context_exa(query: "React hooks examples", tokensNum: 3000)'
Parameters:
query - Code/API search querytokensNum (optional, default: 5000) - Range: 1000-50000Research companies for business info and news.
mcporter call 'exa.company_research_exa(companyName: "Anthropic", numResults: 3)'
Parameters:
companyName - Company namenumResults (optional, default: 5)Six additional tools available by updating config URL:
web_search_advanced_exa - Domain/date filtersdeep_search_exa - Query expansioncrawling_exa - Full page extractionpeople_search_exa - Professional profilesdeep_researcher_start/check - AI research agentEnable all tools:
mcporter config add exa-full "https://mcp.exa.ai/mcp?tools=web_search_exa,web_search_advanced_exa,get_code_context_exa,deep_search_exa,crawling_exa,company_research_exa,people_search_exa,deep_researcher_start,deep_researcher_check"
# Then use:
mcporter call 'exa-full.deep_search_exa(query: "AI safety research")'
type: "fast" for quick lookup, "deep" for thorough researchtokensNum (1000-2000) for focused, higher (5000+) for comprehensive