Agent Feedback Loop
Enables agents to report and query performance metrics to build a community-driven quality database for MCP tools. This server helps agents discover and select the most reliable tools based on success rates and user-reported quality scores.
README
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
pip install agent-feedback-mcp-server
{
"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.
More MCP Servers by AiAgentKarl
| Category | Servers |
|---|---|
| 🔗 Blockchain | Solana |
| 🌍 Data | Weather · Germany · Agriculture · Space · Aviation · EU Companies |
| 🔒 Security | Cybersecurity · Policy Gateway · Audit Trail |
| 🤖 Agent Infra | Memory · Directory · Hub · Reputation |
| 🔬 Research | Academic · LLM Benchmark · Legal |
License
MIT
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