---

name: exa-search description: Use Exa for semantic/neural web search. Exa understands context and returns high-quality results. Use this skill when you need to search the web for documentation, research, or any information that requires understanding meaning rather than just keyword matching. NEVER substitute web_search for Exa - they serve completely different purposes. version: 1.0.0

Exa Semantic Search

Exa provides neural/semantic search via MCP. Use it for high-quality web search that understands context.

When to Use Exa

• Searching for documentation or technical information
• Research requiring semantic understanding
• Finding information where exact keywords are unknown
• Company research and LinkedIn searches
• Deep research tasks

When NOT to Use Exa

• Never use web_search as a substitute - it's basic keyword matching only
• If Exa fails, troubleshoot Exa - don't fall back to web_search

Available Tools

The Exa MCP server provides these tools:

• web_search_exa - Semantic web search
• crawling_exa - Crawl and extract web content
• company_research_exa - Research companies
• linkedin_search_exa - Search LinkedIn profiles
• deep_researcher_start - Start deep research task
• deep_researcher_check - Check deep research status

Configuration

Exa is configured as a remote HTTP MCP in ~/.mcp.json:

Copy{
  "exa": {
    "type": "http",
    "url": "https://mcp.exa.ai/mcp?tools=web_search_exa,crawling_exa,company_research_exa,linkedin_search_exa,deep_researcher_start,deep_researcher_check"
  }
}

Usage Examples

Basic Search

Use the Exa MCP tools directly when semantic search is needed.

Deep Research

1. Start with deep_researcher_start for complex topics
2. Poll with deep_researcher_check until complete
3. Get comprehensive, synthesized results

Critical Rules

1. NEVER replace Exa with web_search - they are fundamentally different
2. NEVER use web_search in Task sub-agents as a substitute for Exa
3. If Exa fails, troubleshoot Exa - do not substitute

Scientific Skill Interleaving

This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:

Graph Theory

• networkx [○] via bicomodule
  • Universal graph hub

Bibliography References

• algorithms: 19 citations in bib.duckdb

Cat# Integration

This skill maps to Cat# = Comod(P) as a bicomodule in the equipment structure:

CopyTrit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826

GF(3) Naturality

The skill participates in triads satisfying:

Copy(-1) + (0) + (+1) ≡ 0 (mod 3)

This ensures compositional coherence in the Cat# equipment structure.