Merit-Systems

web-research

Neural web search and content extraction using x402-protected APIs. Better than WebSearch for deep research and WebFetch for blocked sites. USE FOR: - Deep web research and investigation - Finding similar pages to a reference URL - Extracting clean text from web pages - Scraping sites that block standard fetchers - Getting direct answers to factual questions - Research requiring multiple sources TRIGGERS: - "research", "investigate", "deep dive", "find sources" - "similar to", "pages like", "more like this" - "scrape", "extract content from", "get the text from" - "blocked site", "can't access", "paywall" - "what is", "explain", "answer this" Use agentcash.fetch for stableenrich.dev endpoints. Prefer Exa for semantic/neural search, Firecrawl for direct scraping.

Merit-Systems 10 3 Updated 3mo ago

Resources

1
GitHub

Install

npx skillscat add merit-systems/agentcash-skills/mcp-skills-web-research

Install via the SkillsCat registry.

SKILL.md

Web Research with x402 APIs

Access Exa (neural search) and Firecrawl (web scraping) through x402-protected endpoints.

Setup

See rules/getting-started.md for installation and wallet setup.

Quick Reference

Task Endpoint Price Best For
Neural search https://stableenrich.dev/api/exa/search $0.01 Semantic web search
Find similar https://stableenrich.dev/api/exa/find-similar $0.01 Pages similar to a URL
Extract text https://stableenrich.dev/api/exa/contents $0.002 Clean text from URLs
Direct answers https://stableenrich.dev/api/exa/answer $0.01 Factual Q&A
Scrape page https://stableenrich.dev/api/firecrawl/scrape $0.0126 Single page to markdown
Web search https://stableenrich.dev/api/firecrawl/search $0.0252 Search with scraping

When to Use What

Scenario Tool
General web search WebSearch (free) or Exa ($0.01)
Semantic/conceptual search Exa search
Find pages like X Exa find-similar
Get clean text from URL Exa contents
Scrape blocked/JS-heavy site Firecrawl scrape
Search + scrape results Firecrawl search
Quick fact lookup Exa answer

See rules/when-to-use.md for detailed guidance.

Exa Neural Search

Semantic search that understands meaning, not just keywords:

agentcash.fetch(
  url="https://stableenrich.dev/api/exa/search",
  method="POST",
  body={
    "query": "startups building AI agents for customer support",
    "numResults": 10,
    "type": "neural"
  }
)

Options:

  • query - Search query (required)
  • numResults - Number of results (default: 10, max: 25)
  • type - "neural" (semantic) or "keyword" (traditional)
  • includeDomains - Only search these domains
  • excludeDomains - Skip these domains
  • startPublishedDate / endPublishedDate - Date range filter

Returns: List of URLs with titles, snippets, and relevance scores.

Find Similar Pages

Find pages semantically similar to a reference URL:

agentcash.fetch(
  url="https://stableenrich.dev/api/exa/find-similar",
  method="POST",
  body={
    "url": "https://example.com/article-i-like",
    "numResults": 10
  }
)

Great for:

  • Finding competitor products
  • Discovering related content
  • Expanding research sources

Extract Text Content

Get clean, structured text from URLs:

agentcash.fetch(
  url="https://stableenrich.dev/api/exa/contents",
  method="POST",
  body={
    "urls": [
      "https://example.com/article1",
      "https://example.com/article2"
    ]
  }
)

Options:

  • urls - Array of URLs to extract
  • text - Include full text (default: true)
  • highlights - Include key highlights

Cheapest option ($0.002) when you already have URLs and just need the content.

Direct Answers

Get factual answers to questions:

agentcash.fetch(
  url="https://stableenrich.dev/api/exa/answer",
  method="POST",
  body={
    "query": "What is the population of Tokyo?"
  }
)

Returns a direct answer with source citations. Best for:

  • Factual questions
  • Quick lookups
  • Verification of claims

Firecrawl Scrape

Scrape a single page to clean markdown:

agentcash.fetch(
  url="https://stableenrich.dev/api/firecrawl/scrape",
  method="POST",
  body={
    "url": "https://example.com/page-to-scrape"
  }
)

Options:

  • url - Page to scrape (required)
  • formats - Output formats: ["markdown", "html", "links"]
  • onlyMainContent - Skip nav/footer/ads (default: true)
  • waitFor - Wait ms for JS to render

Advantages over WebFetch:

  • Handles JavaScript-rendered content
  • Bypasses common blocking
  • Extracts main content only
  • LLM-optimized markdown output

Firecrawl Search

Web search with automatic scraping of results:

agentcash.fetch(
  url="https://stableenrich.dev/api/firecrawl/search",
  method="POST",
  body={
    "query": "best practices for react server components",
    "limit": 5
  }
)

Options:

  • query - Search query (required)
  • limit - Number of results (default: 5)
  • scrapeOptions - Options passed to scraper

Returns search results with full scraped content for each.

Workflows

Deep Research

  • (Optional) Check balance: agentcash.get_wallet_info
  • Search broadly with Exa
  • Find related sources with find-similar
  • Extract content from top sources
  • Synthesize findings
agentcash.fetch(
  url="https://stableenrich.dev/api/exa/search",
  method="POST",
  body={"query": "AI agents in healthcare 2024", "numResults": 15}
)
agentcash.fetch(
  url="https://stableenrich.dev/api/exa/find-similar",
  method="POST",
  body={"url": "https://best-article-found.com"}
)
agentcash.fetch(
  url="https://stableenrich.dev/api/exa/contents",
  method="POST",
  body={"urls": ["url1", "url2", "url3"]}
)

Blocked Site Scraping

  • Try WebFetch first (free)
  • If blocked/empty, use Firecrawl with waitFor for JS-heavy sites
agentcash.fetch(
  url="https://stableenrich.dev/api/firecrawl/scrape",
  method="POST",
  body={"url": "https://blocked-site.com/article", "waitFor": 3000}
)

Cost Optimization

  • Use Exa contents ($0.002) when you already have URLs
  • Use WebSearch/WebFetch first (free) and fall back to x402 endpoints
  • Batch URL extraction - pass multiple URLs to Exa contents
  • Limit results - request only as many as needed

Parallel Calls

Independent searches can run in parallel:

# These don't depend on each other
agentcash.fetch(url=".../exa/search", body={"query": "topic A"})
agentcash.fetch(url=".../exa/search", body={"query": "topic B"})