sensitive-info-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| SI_MCP_MODEL | No | Optional model name for AI detection (default: gpt-4o-mini) | |
| OPENAI_API_KEY | No | OpenAI API key for AI-enhanced detection | |
| OPENAI_BASE_URL | No | Optional base URL for OpenAI API (default: https://api.openai.com/v1) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| scan_textA | 检测文本中的敏感信息 Args: text: 待检测文本 enable_ai: 是否启用 AI 语义检测（需配置 OPENAI_API_KEY 环境变量） mask_strategy: 脱敏策略，可选 mask|replace|hash|keep_format|redact Returns: JSON 格式的检测结果列表 |
| mask_textB | 检测并脱敏文本，返回脱敏后的文本 Args: text: 待脱敏文本 mask_strategy: 脱敏策略 mask|replace|hash|keep_format|redact enable_ai: 是否启用 AI 语义检测 Returns: 脱敏后的文本 |
| scan_reportB | 生成完整的 Markdown 扫描报告 Args: text: 待扫描文本 enable_ai: 是否启用 AI 检测 mask_strategy: 脱敏策略 Returns: Markdown 格式的扫描报告 |
| scan_fileB | 扫描文件中的敏感信息 Args: file_path: 文件路径 enable_ai: 是否启用 AI 检测 mask_strategy: 脱敏策略 Returns: JSON 格式的检测结果 |
| mask_fileB | 脱敏文件内容并保存 Args: file_path: 输入文件路径 output_path: 输出文件路径（与 inplace 互斥） mask_strategy: 脱敏策略 enable_ai: 是否启用 AI 检测 inplace: 是否原地覆盖（慎用） Returns: 操作结果 JSON |
| list_rulesA | 列出当前所有内置检测规则 Returns: JSON 格式的规则列表 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose: listing rules, masking files/text, scanning files/text, and generating reports. The only potential overlap (scan_text vs. scan_report) is resolved by different return formats (JSON vs. Markdown).
All tool names follow a consistent verb_noun pattern in snake_case (e.g., list_rules, mask_file, scan_text). No mixing of conventions or irregular names.
Six tools is an appropriate number for a sensitive info scanning and masking server. Each tool covers a necessary operation without redundancy or excessive specialization.
The tool set covers core workflows: scanning (file and text), masking (file and text), report generation, and rule listing. A minor gap is the lack of rule management tools (add/modify rules), but the primary detection and masking functionality is complete.