Metadata-Version: 2.4
Name: agent-feedback-mcp-server
Version: 0.1.0
Summary: Quality signals for MCP tools — agents report results, building a community-driven quality database
Project-URL: Homepage, https://github.com/AiAgentKarl/agent-feedback-mcp-server
Project-URL: Repository, https://github.com/AiAgentKarl/agent-feedback-mcp-server
Author: AiAgentKarl
License: MIT
Keywords: ai-agents,feedback,mcp,quality,ratings,recommendations
Requires-Python: >=3.10
Requires-Dist: mcp>=1.0.0
Requires-Dist: pydantic>=2.0.0
Description-Content-Type: text/markdown

# Agent Feedback Loop 📊

Community-driven quality signals for MCP tools. Agents report tool results, building a quality database that helps all agents pick better tools.

## The Problem

Agents don't know which MCP tools are reliable. They try tools blindly and hope for the best.

## The Solution

Automated feedback: agents report success/failure and quality after each tool call. Over time, a quality database emerges that helps every agent make better decisions.

## Installation

```bash
pip install agent-feedback-mcp-server
```

```json
{
  "mcpServers": {
    "feedback": {
      "command": "uvx",
      "args": ["agent-feedback-mcp-server"]
    }
  }
}
```

## Tools

| Tool | Description |
|------|-------------|
| `report_tool_result` | Report success/failure and quality score |
| `get_tool_quality` | Get quality metrics for a specific tool |
| `get_best_tools` | Find highest-rated tools (optionally by task) |
| `get_trending_tools` | See what's trending recently |

## Network Effect

More agents reporting → Better quality data → Better tool choices → More agents using → More reports. The database gets better with every user.

## License

MIT
