Yahoo Finance MCP — Equity Fundamentals & Analyst Data

nexgendata-apify/yahoo-finance-mcp-server

93

Dominant

3 tools · Source: smithery · Scanned: May 11, 2026

Score breakdown

Findability

25/25

Can AI agents discover this tool? Measures naming quality, keyword overlap with queries, and registry presence.

Clarity

30/35

Can agents understand what this tool does? Measures description quality, action verbs, usage context ("Use this when..."), and return value documentation.

Precision

23/25

Is the interface precise? Measures input schema completeness, type definitions, required fields, enums, defaults, and parameter descriptions.

Efficiency

15/15

Is the tool token-efficient? Measures description length optimization, tool count, and naming conciseness.

Optimization status

All

This server is well-optimized for AI agent discovery. Consider adding enums, defaults, and usage examples for marginal gains.

Expected impact: +1-2 pts

Estimated selection rate

~85%

At 93/100, AI agents select tools like this approximately 85% of the time when choosing between competing alternatives. This server is in the top tier for agent discoverability.

Based on 500-round selection simulation (Pearson r = 0.828). Methodology →

Trust Verification

0Unverified
📋Spec Verified○ Not yet
93/100Spec Score
RequirementScore ≥ 85 on ToolRank Spec Quality analysis
MethodAutomated static analysis of tool definitions, descriptions, parameters, error handling
RenewalRe-verified on every scan (weekly)
🎯Selection Verified○ Not yet
Win Rate
RequirementSelection win rate ≥ 70% in 100-round LLM tournament
MethodClaude Sonnet selects best tool for realistic tasks vs. competing servers
RenewalRe-tested monthly; expires if win rate drops below 60%
Runtime Verified○ Not yet
Status
RequirementTask success rate ≥ 90%, error rate < 5%, avg latency < 2s
MethodEnd-to-end execution tests in sandboxed environment
RenewalContinuously monitored; revoked on sustained failure

Score history

93
Apr 11
93
Apr 12
93
Apr 13
93
Apr 14
93
Apr 15
93
Apr 16
93
Apr 17
93
Apr 18
93
Apr 19
93
Apr 20
93
Apr 21
93
Apr 26
93
Apr 27
93
May 4
93
May 5
93
May 6
93
May 7
93
May 8
93
May 9
93
May 10
93
May 11

Tracked daily. 21 data points.

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