In-depth architectural comparison of the Generect MCP and Quality Screener MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Generect MCP
Developer Tools · Local stdio
Quality: 57/100 (Good) | Auth: No auth required
Quality Screener
Developer Tools · Local stdio
Quality: 45/100 (Fair) | Auth: No auth required
Verdict Summary: Choose Generect MCP if you need specialized Developer Tools tools running via a local process. Choose Quality Screener if your workspace requires Developer Tools integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Generect MCP when:
You need dedicated capabilities in the Developer Tools domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Generect MCP is categorized under Developer Tools and uses a local stdio subprocess. In contrast, Quality Screener belongs to Developer Tools using local stdio subprocess. Select Generect MCP when you need capabilities focused on developer tools and Quality Screener when you require tools for developer tools.
per returned row (cheapest way to see real people)
enrich_lead
per record found
resolve_profile
per **resolved** profile — the cheapest call here; an unresolvable reference is free
enrich_company
per record found
+4 more tools listed on main page
Quality Screener Tools (23)
auth_status
Whether a token is present and which user it authenticates as.
account_profile
The signed-in user's profile (email, username, organization).
health
API and database health check.
scores_top
Top tickers by quality score, as a `{ticker: score}` map.
scores_list
List scored tickers with optional filters.
scores_show
Full score row(s) for a single ticker.
scores_for_tickers
Current scores for a specific list of tickers, under default scoring or a saved scoring system. Unknown tickers are omitted.
scores_statistics
Min / max / average score statistics for a filtered universe.
scores_market_cap
Aggregated total market cap (USD) for a filtered universe.
score_compute
Compute custom scores from a `CustomScoreConfig`. `scoring_universe` picks the peer group (changes the scores); the other filters select rows (do not).
screen_share
Persist a `CustomScoreConfig` and return a public, copy-pasteable share link (`url`, `slug`, `created`, `view_count`). Content-addressed: an identical config returns the same link.
filters_list
Available filter values (sectors, industries, countries, currencies, exchanges).