Overview

The MCP Skill exposes the MCP API at mcp.exa.ai/mcp, giving you access to web search, deep research, code context, crawling, and LinkedIn search. It bundles specialized tools—web_search_exa, web_search_advanced_exa, get_code_context_exa, deep_search_exa, crawling_exa, company_research_exa, linkedin_search_exa, deep_researcher_start, and deep_researcher_check—for fast, multi-source intelligence gathering. This enables rapid insight generation for product, market, and competitive analysis.

How This Skill Works

Requests are sent to the MCP endpoint and dispatched to the appropriate tool based on your query. Tools return results with sourcing and context, and you can chain deep_researcher_start and deep_researcher_check for ongoing investigations. You can mix web_search and deep_search workflows, and pull code context when needed with get_code_context_exa.

When to Use It

• When you need up-to-date web intelligence on a competitor or market using web_search_exa and web_search_advanced_exa.
• When you require deep, multi-source research and source crawling with deep_search_exa and crawling_exa.
• When you need code context or snippets for a coding task using get_code_context_exa.
• When you’re mapping company profiles or doing background checks with company_research_exa.
• When locating people or orgs on LinkedIn for outreach using linkedin_search_exa.

Quick Start

1. Step 1: Connect to the MCP endpoint at mcp.exa.ai/mcp and select the tools you’ll use (e.g., web_search_exa, deep_search_exa, get_code_context_exa).
2. Step 2: Run a targeted query with web_search_exa or web_search_advanced_exa; start a deep_researcher session if you’re pursuing a long-running project.
3. Step 3: Review results, validate with deep_researcher_check, and extract code context or sources as needed for your deliverable.

Best Practices

• Define a clear objective and map it to the MCP tools you will use (e.g., web_search_exa for surface intel, deep_search_exa for deeper digging).
• Use deep_researcher_start for long-running investigations and deep_researcher_check to iterate results over time.
• Cross-validate findings by combining web_search_exa with deep_search_exa and verify sources.
• Save and cite sources from each tool; maintain a small bibliography for audits.
• Respect platform policies and data privacy when using crawling and LinkedIn-related tools.

Example Use Cases

• Competitive feature landscape audit by running web_search_exa and deep_search_exa to map capabilities and timelines.
• API integration research using get_code_context_exa to collect relevant code samples and usage patterns.
• Industry trend synthesis with crawling_exa and deep_search_exa to assemble multi-source reports.
• Company background mapping with company_research_exa and linkedin_search_exa for market-entry planning.
• Targeted talent outreach using linkedin_search_exa to identify and verify potential contacts.

Frequently Asked Questions