An open-source MCP server that provides LLM access to the Sauce Labs API
Emerging. No concerning findings. Grades remain capped until the project builds reputation through adoption. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.
How we verified
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⚡ Connect GitHub → continuous verification on every pushwhy connect →Who stands behind it
saucelabs
Source: modelscope
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Install from
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ALTERNATE_URLSAUCE_ACCESS_KEY"": "your-sauce-access-key"SAUCE_USERNAME"": "your-sauce-username",SAUCE_REGIONUS_WEST Data centre region: US_WEST, US_EAST, EU_CENTRALSAUCE_MCP_MAX_RESPONSE_ITEMSconfigurable via )RDC_OPENAPI_SPEC_URLTool annotations
No tools have read-only/destructive annotations
Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.
All four hints declared on every tool
73/73 tools missing one or more hints — get_account_info (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); lookup_teams (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); get_team (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +70 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.
For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.
Tool inputs are validated
72/73 tool handlers declare input schemas (99%)
Declare an inputSchema with zod/joi/yup on every tool definition.
Tool test coverage
40/73 tools referenced in tests (55%)
Write tests that reference each tool by name so every tool has at least one test.
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