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mrexodia

User Feedback

by mrexodia
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

User Feedback MCP

Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor. This is especially useful for developing desktop applications that require complex user interactions to test.

Screenshot showing the feedback UI

Prompt Engineering

For the best results, add the following to your custom prompt:

Before completing the task, use the user_feedback MCP tool to ask the user for feedback.

This will ensure Cline uses this MCP server to request user feedback before marking the task as completed.

Related MCP server: mcp-connect

.user-feedback.json

Hitting Save Configuration creates a .user-feedback.json file in your project directory that looks like this:

{
  "command": "npm run dev",
  "execute_automatically": false
}

This configuration will be loaded on startup and if execute_automatically is enabled your command will be instantly executed (you will not have to click Run manually). For multi-step commands you should use something like Task.

Installation (Cline)

To install the MCP server in Cline, follow these steps (see screenshot):

Screenshot showing installation steps

  1. Install uv globally:

    • Windows: pip install uv

    • Linux/Mac: curl -LsSf https://astral.sh/uv/install.sh | sh

  2. Clone this repository, for this example C:\MCP\user-feedback-mcp.

  3. Navigate to the Cline MCP Servers configuration (see screenshot).

  4. Click on the Installed tab.

  5. Click on Configure MCP Servers, which will open cline_mcp_settings.json.

  6. Add the user-feedback-mcp server:

{
  "mcpServers": {
    "github.com/mrexodia/user-feedback-mcp": {
      "command": "uv",
      "args": [
        "--directory",
        "c:\\MCP\\user-feedback-mcp",
        "run",
        "server.py"
      ],
      "timeout": 600,
      "autoApprove": [
        "user_feedback"
      ]
    }
  }
}

Development

uv run fastmcp dev server.py

This will open a web interface at http://localhost:5173 and allow you to interact with the MCP tools for testing.

Available tools

<use_mcp_tool>
<server_name>github.com/mrexodia/user-feedback-mcp</server_name>
<tool_name>user_feedback</tool_name>
<arguments>
{
  "project_directory": "C:/MCP/user-feedback-mcp",
  "summary": "I've implemented the changes you requested."
}
</arguments>
</use_mcp_tool>

Available Tools

1 tool
user_feedbackC

Request user feedback for a given project directory and summary

ParametersJSON Schema
NameRequiredDescriptionDefault
project_directoryYesFull path to the project directory
summaryYesShort, one-line summary of the changes

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'requests' feedback but doesn't explain how this is done (e.g., via UI prompt, email, logging), what permissions are needed, whether it's interactive or automated, or what happens after the request. This leaves critical behavioral aspects unspecified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like how feedback is requested or what the tool returns, leaving gaps in understanding the tool's operation and results. This is inadequate for a tool with potential complexity in feedback mechanisms.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with clear descriptions for both parameters (project directory path and summary). The description adds no additional meaning beyond the schema, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating further.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Request user feedback') and specifies the target ('for a given project directory and summary'), making the purpose understandable. However, it doesn't distinguish from siblings since none exist, and 'request' could be interpreted as initiating a feedback collection process rather than retrieving existing feedback, which is somewhat ambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool, such as the context for requesting feedback, prerequisites, or alternatives. With no sibling tools, this isn't a major issue, but it lacks any usage context, leaving the agent to infer appropriate scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.1/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'user_feedback' has a singular, clear purpose, so an agent cannot misselect among alternatives.

Naming Consistency5/5

The single tool name 'user_feedback' follows a consistent snake_case pattern. Since there is only one tool, there is no inconsistency in naming conventions to evaluate.

Tool Count2/5

A single tool is too few for most server purposes, as it limits functionality and suggests a thin or incomplete surface. For a server named 'User Feedback', one tool may not adequately cover potential operations like viewing, managing, or analyzing feedback.

Completeness2/5

The tool set is severely incomplete for a 'User Feedback' domain. It only provides a way to request feedback, missing essential operations such as retrieving, updating, deleting, or listing feedback, which are necessary for a full CRUD lifecycle.

Maintenance

ActivityInactive
ResponsivenessResponsive

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