Can this skill be used for deep research tasks?

Yes, it includes specialized tools to start and poll deep research tasks that synthesize information from multiple sources.

Should I use web_search if Exa fails?

No, the skill instructions specifically advise troubleshooting the Exa connection rather than falling back to basic web search to ensure result quality.

How is Exa different from the default web search?

Exa uses neural/semantic understanding to find results based on meaning and context, whereas the default search relies on simple keyword matching.

Does this skill support LinkedIn or company-specific searches?

Absolutely, it features dedicated tools for LinkedIn profile searches and detailed company research.

How do I configure the Exa MCP connection?

You need to add the Exa HTTP MCP URL to your ~/.mcp.json configuration file as a remote service.

Exa Semantic Search

Name: Exa Semantic Search
Author: plurigrid

byplurigrid

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Web Scraping & Data Collection

Performs neural, context-aware web searches and deep research tasks to find high-quality information that keyword matching misses.

About

The Exa Semantic Search skill equips Claude with advanced neural search capabilities through the Exa MCP. Unlike standard keyword-based search engines, Exa understands the semantic intent behind queries, making it ideal for finding technical documentation, conducting company research, and performing deep, synthesized investigations. It includes specialized tools for crawling web content, searching LinkedIn profiles, and managing multi-step research agents, ensuring high-quality data retrieval for complex development and research workflows.

Key Features

Context-aware neural search for superior results over keyword matching
Deep research capabilities with autonomous status polling and synthesis
High-fidelity technical documentation and research retrieval
Specialized tools for company profiles and LinkedIn search
Integrated web crawling and content extraction
2 GitHub stars

Use Cases

Conducting comprehensive market or company research
Finding specific technical solutions when exact keywords are unknown
Automating the retrieval and synthesis of multi-source academic or technical documentation

About

Key Features

Context-aware neural search for superior results over keyword matching
Deep research capabilities with autonomous status polling and synthesis
High-fidelity technical documentation and research retrieval
Specialized tools for company profiles and LinkedIn search
Integrated web crawling and content extraction
2 GitHub stars

Use Cases

Conducting comprehensive market or company research
Finding specific technical solutions when exact keywords are unknown
Automating the retrieval and synthesis of multi-source academic or technical documentation