Websets MCP

Websets MCP: Build and enrich collections of web entities with AI

Websets MCP Server enables AI assistants like Claude to create, search, and enrich collections of web entities (companies, people, research papers, articles) through the Exa Websets API. Automatically discover entities, verify them against criteria, and extract custom data with AI-powered enrichments. Examples of what you can do with Websets MCP:

Find and verify AI startups in San Francisco with funding over $10M
Create a list of research papers on quantum computing and extract key findings
Build a database of companies in specific industries and enrich with CEO names, revenue, and employee counts
Monitor industries for new companies matching your criteria

Works with Cursor and Claude Code! Use the HTTP-based configuration format below.

Websets MCP provides powerful tools for entity search, verification, and data enrichment, making it easy to build custom datasets for research, sales, recruiting, and more.

Remote Websets MCP

Connect directly to Exa’s hosted Websets MCP server using this URL:

https://websetsmcp.exa.ai/mcp

You must include your Exa API key in the URL:

https://websetsmcp.exa.ai/mcp?exaApiKey=YOUR_EXA_API_KEY

Note: Unlike the standard Exa MCP, the Websets MCP does not require a separate Websets/Smithery key when using the custom domain. Only your Exa API key is required.

Claude Desktop Configuration for Remote MCP

Add this to your Claude Desktop configuration file:

{
  "mcpServers": {
    "websets": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://websetsmcp.exa.ai/mcp?exaApiKey=YOUR_EXA_API_KEY"
      ]
    }
  }
}

Replace YOUR_EXA_API_KEY with your actual Exa API key.

Cursor and Claude Code Configuration for Remote MCP

For Cursor and Claude Code, use this HTTP-based configuration format:

{
  "mcpServers": {
    "websets": {
      "type": "http",
      "url": "https://websetsmcp.exa.ai/mcp?exaApiKey=YOUR_EXA_API_KEY",
      "headers": {}
    }
  }
}

Replace YOUR_EXA_API_KEY with your actual Exa API key.

Available Tools

Websets MCP includes 14 specialized tools for managing websets, searches, enrichments, and monitors:

Webset Management

Tool	Description
`create_webset`	Create a new webset collection with automatic search and optional enrichments. Specify your search query, criteria for filtering results, and data fields to extract
`list_websets`	List all websets in your account with pagination support
`get_webset`	Get detailed information about a specific webset including its status, searches, enrichments, and items
`update_webset`	Update a webset’s metadata with custom key-value pairs

Item Management

Tool	Description
`list_webset_items`	List all items (entities) in a webset with their properties and enrichment data
`get_item`	Get detailed information about a specific item in a webset

Search Operations

Tool	Description
`create_search`	Create a new search to find and add entities to a webset. Specify entity type (company, person, paper, article), search query, and filtering criteria
`get_search`	Check the status and results of a search operation
`cancel_search`	Cancel a running search operation

Enrichment Operations

Tool	Description
`create_enrichment`	Create a new enrichment to extract custom data from webset items. Supports text, number, date, email, phone, URL, and options formats
`get_enrichment`	Get details about a specific enrichment including its progress and status
`delete_enrichment`	Delete an enrichment and all its extracted data
`cancel_enrichment`	Cancel a running enrichment operation

Monitor Operations

Tool	Description
`create_monitor`	Create a monitor to automatically update a webset on a schedule using cron expressions. Monitors run searches periodically to find new entities

Getting Started

Get your Exa API key

Usage Examples

Once configured, you can ask your AI assistant to perform webset operations:

Creating a Webset

Create a webset of AI startups in San Francisco founded after 2020. 
Find 10 companies and enrich with CEO name and funding amount.

This will use create_webset to:

Search for AI startups in San Francisco
Filter for companies founded after 2020
Automatically enrich each company with CEO name and funding amount

Searching for Entities

Search for 5 more AI companies in the existing webset that have 
raised Series A or later funding.

This will use create_search to add more companies matching specific criteria.

Creating Enrichments

Add an enrichment to extract the number of employees for each company 
in the webset.

This will use create_enrichment to extract employee counts.

Setting Up Monitors

Create a monitor to check for new AI startups in San Francisco 
every Monday at 9am.

This will use create_monitor to automatically update your webset weekly.

Listing and Viewing Results

Show me all the companies in my AI startups webset.

This will use list_webset_items to display the collected entities with their enrichment data.

Key Features

Entity Types

Websets support multiple entity types:

Companies - Search and enrich company data
People - Find and verify individuals with specific criteria
Research Papers - Discover academic papers and extract key information
Articles - Find articles and blog posts on specific topics
Custom - Define your own entity type

Enrichment Formats

Extract data in multiple formats:

text - Free-form text (e.g., company description, CEO name)
number - Numeric values (e.g., employee count, revenue)
date - Dates (e.g., founding date, last funding round)
email - Email addresses
phone - Phone numbers
url - Website URLs
options - Multiple choice selection from predefined options (e.g., company stage: Seed, Series A, Series B)

Search Criteria

Use natural language criteria to filter search results:

“Founded after 2020”
“Has raised more than $10M in funding”
“Located in the United States”
“Has more than 50 employees”

The AI will evaluate each potential entity against your criteria and only include matches.

Automated Monitoring

Set up monitors with cron expressions to keep your websets up-to-date:

0 9 * * 1 - Every Monday at 9:00 AM
0 0 * * * - Every day at midnight
0 */6 * * * - Every 6 hours

Monitors automatically run searches and add new matching entities to your webset.

Advanced Examples

Building a Company Database

Create a webset of B2B SaaS companies with:
- Query: "B2B SaaS companies in New York"
- Criteria: "Has raised Series A or later funding"
- Enrichments: 
  - CEO name (text)
  - Employee count (number)
  - Funding stage (options: Seed, Series A, Series B, Series C+)
  - Latest funding date (date)
  - Company website (url)

Research Paper Collection

Create a webset of machine learning research papers with:
- Query: "Recent papers on transformer models in NLP"
- Criteria: "Published in 2024 or 2025"
- Enrichments:
  - Lead author (text)
  - Publication date (date)
  - Key findings (text)
  - Citation count (number)

People Search for Recruiting

Create a webset of potential candidates:
- Query: "Senior ML engineers in San Francisco Bay Area"
- Criteria: "Has 5+ years of experience in machine learning"
- Enrichments:
  - Current company (text)
  - LinkedIn profile (url)
  - Email address (email)
  - Years of experience (number)

API Integration

Websets MCP provides a seamless interface to the Websets API. For more detailed information about the underlying API, visit:

Configuration Details

Claude Desktop (macOS)

Configuration file location:

~/Library/Application\ Support/Claude/claude_desktop_config.json

Claude Desktop (Windows)

Configuration file location:

%APPDATA%\Claude\claude_desktop_config.json

Required Parameters

When using the hosted MCP server at https://websetsmcp.exa.ai/mcp, you must include your Exa API key:

https://websetsmcp.exa.ai/mcp?exaApiKey=YOUR_EXA_API_KEY

Parameter Formats

When creating websets, searches, enrichments, and monitors through natural language with your AI assistant, the following formats are automatically used: Search Criteria Format:

[
  {"description": "Founded after 2020"},
  {"description": "Has raised more than $10M"}
]

Enrichment Format:

[
  {"description": "CEO name", "format": "text"},
  {"description": "Company stage", "format": "options", "options": [
    {"label": "Seed"},
    {"label": "Series A"},
    {"label": "Series B"}
  ]}
]

Entity Type Format:

{"type": "company"}

Cron Expression Format (for Monitors):

"0 9 * * 1"  (Every Monday at 9:00 AM)

Tips for Best Results

Be specific with search queries - The more specific your query, the better the results
Use clear criteria - Write criteria in simple, declarative sentences
Choose appropriate enrichment formats - Use “options” format when you want to categorize data
Start small - Begin with a small search count (5-10 items) to test your query and criteria
Monitor long-running operations - Use get_search and get_enrichment to check progress
Use external IDs - Provide your own IDs to websets for easier reference in your application

Troubleshooting

Common Issues

Issue: Enrichment not extracting the right data

Solution: Make your enrichment description more specific and include example formats

Issue: Search returning no results

Solution: Try broadening your search criteria or making your query less specific

Issue: Monitor not running

Solution: Verify your cron expression format (5 fields: minute hour day month weekday)

Getting Help

Additional Resources

Websets Dashboard - Visual interface for managing websets
Websets API Reference - Complete API documentation
Websets Examples - Example queries and use cases
Exa Search API - The underlying search technology

Getting Started

API Reference

Concepts

Integrations

Admin

​Websets MCP: Build and enrich collections of web entities with AI

​Remote Websets MCP

​Claude Desktop Configuration for Remote MCP

​Cursor and Claude Code Configuration for Remote MCP

​Available Tools

​Webset Management

​Item Management

​Search Operations

​Enrichment Operations

​Monitor Operations

​Getting Started

Get your Exa API key

​Usage Examples

​Creating a Webset

​Searching for Entities

​Creating Enrichments

​Setting Up Monitors

​Listing and Viewing Results

​Key Features

​Entity Types

​Enrichment Formats

​Search Criteria

​Automated Monitoring

​Advanced Examples

​Building a Company Database

​Research Paper Collection

​People Search for Recruiting

​API Integration

​Configuration Details

​Claude Desktop (macOS)

​Claude Desktop (Windows)

​Required Parameters

​Parameter Formats

​Tips for Best Results

​Troubleshooting

​Common Issues

​Getting Help

​Additional Resources

Websets MCP: Build and enrich collections of web entities with AI

Remote Websets MCP

Claude Desktop Configuration for Remote MCP

Cursor and Claude Code Configuration for Remote MCP

Available Tools

Webset Management

Item Management

Search Operations

Enrichment Operations

Monitor Operations

Getting Started

Usage Examples

Creating a Webset

Searching for Entities

Creating Enrichments

Setting Up Monitors

Listing and Viewing Results

Key Features

Entity Types

Enrichment Formats

Search Criteria

Automated Monitoring

Advanced Examples

Building a Company Database

Research Paper Collection

People Search for Recruiting

API Integration

Configuration Details

Claude Desktop (macOS)

Claude Desktop (Windows)

Required Parameters

Parameter Formats

Tips for Best Results

Troubleshooting

Common Issues

Getting Help

Additional Resources