mcp-feedback-enhanced-community-fix
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| MCP_DEBUG | No | 是否输出调试日志 | false |
| MCP_LANGUAGE | No | 界面语言 | 自动检测 |
| MCP_WEB_HOST | No | Web UI 监听地址 | 127.0.0.1 |
| MCP_WEB_PORT | No | Web UI 端口 | 8765 |
| MCP_DESKTOP_MODE | No | 是否启用桌面模式 | false |
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": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| interactive_feedbackA | Interactive feedback collection tool for LLM agents. USAGE RULES:
|
| get_system_infoA | 獲取系統環境資訊 Returns: str: JSON 格式的系統資訊 |
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 2 tools
The two tools serve entirely distinct purposes: one retrieves system information, the other collects feedback. There is no overlap or ambiguity.
Both tool names follow a consistent verb_noun pattern using snake_case ('get_system_info' and 'interactive_feedback'), making them predictable.
With only two tools, the server feels minimal. However, for a focused feedback-collection purpose with a system info utility, the count is acceptable, though many servers would offer more.
The server covers its stated domain (feedback collection and system info) adequately. The feedback tool is designed for repeated use mid-task, so no additional CRUD tools are needed. Minor gap: no way to retrieve past feedback, but rules imply continuous interaction.