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AiAgentKarl

Agent Feedback Loop

by AiAgentKarl
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

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.

Related MCP server: disvr

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

→ Full catalog (40+ servers)

License

MIT

Install Server
A
license - permissive license
A
quality
D
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Tools

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  • disvr

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  • hive-exp

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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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