MCP-Confirm
Related Servers
Alternatives to MCP-Confirm
No user-submitted related servers found.
Related Servers
- AlicenseBqualityCmaintenanceAn MCP server that provides a user confirmation interface for AI assistants via terminal.110 npm4MIT
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- AlicenseAqualityAmaintenanceAn MCP server that enables human-in-the-loop elicitation, letting AI agents ask users questions via tools like elicit_confirm and elicit_form, with diagnostics to verify host elicitation support.31Apache 2.0
- AlicenseAqualityAmaintenanceAn MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.215Apache 2.0
- AlicenseNot gradedqualityCmaintenanceA cross-platform MCP server that provides native popup windows for AI agents to gather user feedback, input, and safety confirmations. It enables agents to present interactive questionnaires and secure confirmation prompts for sensitive operations like file deletion or code execution.13MIT
- AlicenseNot gradedqualityDmaintenanceMCP server enabling AI agents to request user feedback during tasks, reducing wasted API calls. Optimized for data sync workflows with tools for audience sync confirmation, DMP verification, and rollback confirmation.MIT
TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose with no ambiguity. For example, ask_yes_no handles simple binary questions, clarify_intent addresses ambiguous requests, confirm_action verifies impactful operations, and verify_understanding checks comprehension—all serving different confirmation needs without overlap.
All tools follow a consistent verb_noun pattern with clear, descriptive names. Examples include analyze_logs, search_logs, collect_rating, and verify_understanding, maintaining uniformity throughout the set without any deviations in style or structure.
With 8 tools, the server is well-scoped for handling user confirmation and verification tasks. Each tool earns its place by covering distinct aspects like questioning, clarification, logging, and feedback, avoiding both bloat and insufficiency.
The tool set provides complete coverage for the confirmation domain, including standard confirmations (ask_yes_no, confirm_action), intent handling (clarify_intent, verify_understanding), feedback collection (collect_rating), logging (analyze_logs, search_logs), and customization (elicit_custom), with no apparent gaps.