freshcontext-mcp
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TDQS
Scored across 22 tools
The single-source extract_* tools are reasonably distinct, but the five composite 'landscape' tools overlap heavily. extract_landscape and extract_idea_landscape are near-duplicates (both take a project idea and query YC, GitHub, HN, Reddit, Product Hunt, and packages), and greed_landscape/gov_landscape/company_landscape share USASpending/changelog/GDELT sources, making selection ambiguous.
Almost everything follows snake_case verb_noun (extract_x, search_x, package_trends, evaluate_context), with a systematic extract_ prefix for data tools and a _landscape suffix for composites. Minor deviation in that the composite naming isn't applied uniformly, but overall the pattern is predictable.
22 tools is on the heavy end and the redundancy among composites inflates the count beyond the useful surface. extract_yc is a dead tool that only returns an error, which is a wasted slot for clients.
The surface covers a wide range of data sources (code, research, finance, jobs, gov contracts, news) plus a dedicated evaluation path, so most intelligence-gathering needs are met. The main gap is the disabled extract_yc leaving YC data only reachable indirectly via the composite tools.