index.guru
partial
Claude Code
intent
What does index.guru do and who is it for? Explain it back to me.
23steps
117.2sduration
$1.6273cost
345,251tokens
28 steps5 reasoning steps12 searches
home
docs
docs
search
search
docs
search
search
search
home
openapi
search
search
/browse
/api/content-types
search
search
search
.well-known/mcp
search
mcp-path
search
/help
100%
on-site discovery
64%
reliability
82%
link following
path origin
- previous resource82%
- prior knowledge18%
insight
The agent partially fulfilled the task by identifying what index.guru does (an AI directory spanning social platforms) and who it serves, but could not find pricing or business model information despite multiple search attempts and direct site navigation. The site's limited public-facing content—relying on API schemas and metadata rather than HTML pages—forced the agent to assemble meaning from technical artifacts and prior knowledge rather than from intentionally published copy.
- ›Step [1] (homepage fetch) and step [3] (about page) returned rendered HTML but no substantive copy explaining the service, pricing, or business model—they appear to be client-side SPA shells without static content, making them unhelpful for understanding despite being on-site.
- ›Steps [12] and [18] (OpenAPI schema and content-types endpoint) were the only content-bearing sources; they revealed what the directory catalogs (X accounts, Telegram bots, Instagram accounts, YouTube channels, etc.) through structured API data, not marketing copy. The agent had to reverse-engineer the value proposition from API field names and schema structure.
- ›Step [23] (MCP server card) provided a one-sentence description ('Search and browse the index.guru directory') but no pricing, business model, or differentiation—the site's machine-readable metadata is sparse.
- ›Web searches (steps 4–6, 8–11, 14–15, 19–26) returned competitor comparisons and unrelated products (IndexGuru SEO tool) but no direct information about index.guru's pricing, monetization, or founders, indicating the service has minimal public visibility and no published business documentation online.
- ›The agent correctly inferred uniqueness (multi-platform social media focus vs. web-app-only competitors) from API content types, but this was a reconstructive effort from technical data, not from a published positioning statement or feature comparison.
- ›Pricing and business model gaps are genuine site limitations: no /pricing endpoint, no footer links, no public documentation—the site does not surface this information in any fetchable form.
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