ChuangSi AI Model Content Protection (chuangsiaihub/chuangsi-mcp-python) is an MCP server listed on the M8ven Trust Index. M8ven has not graded it: there is no public source to read and no endpoint we can reach, so there is nothing for us to inspect. No publisher has claimed this listing.
Provides real-time content safety protection for large language models by detecting and preventing risks in both input and output content across multiple dimensions including compliance, ethics, and security.
Limited view. Automated analysis covers part of this stack. Findings reflect what we verified. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.
Limited view: static analysis for Python is partially covered.
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chuangsiaihub
Source: Glama
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Tool 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
2/2 tools missing one or more hints — input_guardrail (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); output_guardrail (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint). 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 handlers catch errors
Only 0/2 tool handlers wrap calls in try/catch (0%)
Wrap each tool handler body in try/catch and return a structured error response.
Tests exist
No test files found
Add tests that exercise each declared tool.
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