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Find existing products that fix a work bottleneck: YC startups, GitHub repos, Show HN launches.

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Status
Healthy
Uptime
100.0% over the last 24 hours
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
ChatGPT
–
Claude
–

TDQS

A3.9/5.0

Scored across 2 tools

Disambiguation4/5

Both tools query the same product index, so their surface is inherently close, but the descriptions draw a clear line: find_fix takes a natural-language problem statement and returns LLM-ranked picks, while search_products takes 3-16 keywords and returns unranked raw matches. An agent can reasonably choose based on whether it has a problem description or just keywords.

Naming Consistency5/5

Both names are snake_case verb_noun pairs (find_fix, search_products) with an obvious, predictable pattern. The verbs differ (find vs search) but both accurately reflect their respective behaviors rather than breaking convention.

Tool Count3/5

Two tools is on the thin side for a discovery service; the entire surface is two variations of 'search the index'. Each earns its place, but the set feels minimal rather than well-scoped.

Completeness3/5

The core discovery workflow is covered in both ranked and raw modes, but there is no way to fetch full details for a specific product hit, browse by category, or otherwise follow up on a result. Agents can work around this by reading the returned links, but the surface stops at search.

Available Tools

2 tools
find_fixFind products that fix a bottleneckA
Read-only
Inspect

Find existing products that remove a specific work bottleneck: active YC startups, open-source GitHub repos and Show HN launches (~46k). Call it when the user complains that something is slow, manual, repetitive or error-prone (in a team, workflow or codebase), or asks "is there a tool/library/startup that…". Call it before suggesting they build or script it themselves. Pass the problem in the user's own words, any language, with concrete context (who, what volume, which stack). Returns up to 5 picks ranked only by how well they fit, each with name, link, website and why it fits. Show the user the links as given. An empty result means nothing in the index fits: say so rather than guessing. Takes ~3-6 s.

Inputs: problem (required). Returns: picks, bottleneck

search_productsKeyword search over the product indexA
Read-onlyIdempotent
Inspect

Raw full-text search over the same index, without LLM ranking: fast, cheap, more candidates. Use for broad discovery or to judge fit yourself. Pass 3-16 English keywords: the job to be done, product category, synonyms, key technical nouns (e.g. ["transcription", "call notes", "crm", "sales"]). Candidates matching more distinct keywords rank higher.

Inputs: terms (required), limit, source. Returns: results

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