MCP server exposing the wavexis browser automation library to LLMs — 220 tools, 13 capability tiers, zero Node.js
WaveXisMCP exposes 10 tools with generally consistent naming (verb-prefixed) and parameter descriptions. However, output schemas are entirely absent from the provided source, none of the tools document what they return, violating a critical A+ pattern. Parameter descriptions are present but terse (averaging ~30 chars), falling below the 72-char baseline for A+ tools. Tool descriptions are more substantial (averaging ~80 chars), but lack guidance on when to use each tool vs. alternatives (e.g., when to choose wavexis_perf_trace vs wavexis_perf_profile). Schema quality is hampered by lack of explicit constraints (enums, min/max bounds) on most parameters. The wavexis_act tool is the highest-risk operation (WRITE classification) but lacks a confirmation/dry-run pattern. Error handling guidance is not evident in the provided code. Overall, the server is solidly above C-grade due to consistent naming and parameter presence, but falls short of B-grade (70+) because output schemas are undocumented and descriptions lack LLM optimization.
Execute a natural language instruction on the current page (M1). Takes an a11y snapshot, matches the instruction to an element, and performs the detected action (click, type, fill, hover).
Get CSS rules from a specific stylesheet.
Get inline and matched CSS styles for an element.
List all stylesheets loaded by the page.
Get JavaScript code coverage.
Get CSS code coverage.
Capture a heap snapshot.
Output schemas completely undocumented. No tool defines what it returns (fields, types, pagination info). LLMs cannot plan downstream calls or extract relevant data without return type documentation.
Parameter descriptions are present but minimal (avg ~30 chars). They lack actionable guidance on format, constraints, or when parameters are required vs optional. E.g., 'Session reference parameter' does not explain what a session_id is, how to obtain it, or what format it accepts.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 45 | 2026-07-28+ | v2 |
Get performance metrics (LCP, FCP, CLS, TTFB, DOMNodes, etc.).
Capture a CPU profile.
Capture a performance trace.
No input constraints (enums, regex patterns, min/max) visible in schemas. Parameters like 'duration_ms' and 'output_path' accept unbounded strings/integers without validation guidance. LLMs may pass absurd values (negative durations, invalid paths).
wavexis_act is a WRITE tool (destructive, mutates page state) but lacks a confirmation/dry-run pattern or idempotency guarantee. Agents can accidentally click wrong elements or fill forms with incorrect data. No recovery path documented.
No error handling guidance provided. Tools do not document what errors are retryable, what require user intervention, or what are fatal. E.g., if session_id is invalid, should the agent retry or call a discovery tool first?
Tool descriptions lack context on when to use each tool. E.g., 'wavexis_perf_trace' and 'wavexis_perf_profile' both capture performance data, but the descriptions don't explain the difference or when an agent should pick one over the other.