Agent Feedback Loop
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Agent Feedback Loopfind the most reliable tools for web searching"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Agent Feedback Loop ๐
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 success/failure and quality score |
| Get quality metrics for a specific tool |
| Find highest-rated tools (optionally by task) |
| See what's trending recently |
Network Effect
More agents reporting โ Better quality data โ Better tool choices โ More agents using โ More reports. The database gets better with every user.
More MCP Servers by AiAgentKarl
Category | Servers |
๐ Blockchain | |
๐ Data | Weather ยท Germany ยท Agriculture ยท Space ยท Aviation ยท EU Companies |
๐ Security | |
๐ค Agent Infra | Memory ยท Directory ยท Hub ยท Reputation |
๐ฌ Research | Academic ยท LLM Benchmark ยท Legal |
โ Full catalog (40+ servers)
License
MIT
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MCP directory API
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curl -X GET 'https://glama.ai/api/mcp/v1/servers/AiAgentKarl/agent-feedback-mcp-server'
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