Schema | Agent Feedback Loop

Agent Feedback Loop

Describes the environment variables required to run the server.

Name	Required	Description	Default
No arguments

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": false }
`prompts`	{ "listChanged": false }
`resources`	{ "subscribe": false, "listChanged": false }
`experimental`	{}

Functions exposed to the LLM to take actions

Name	Description
report_tool_resultA	Report the result of using an MCP tool. Helps build a quality database so agents can discover which tools work best for which tasks. Args: tool_name: Name of the tool used (e.g. "get_weather") success: Whether the tool call was successful quality_score: Quality rating 1-10 (10 = perfect) task_description: What you were trying to do server_name: Which MCP server the tool belongs to response_time_ms: How long the call took in milliseconds error_message: Error message if the call failed
get_tool_qualityA	Get quality metrics for a specific MCP tool. Shows success rate, average quality score, and recent feedback. Args: tool_name: Name of the tool to check
get_best_toolsB	Get the highest-rated MCP tools, optionally filtered by task type. Shows the best tools based on community feedback data. Args: task: Filter by task description keyword (optional) limit: Max results (default: 10)
get_trending_toolsB	Get trending MCP tools based on recent usage and feedback. Shows which tools are being used most and rated highest recently. Args: days: Look back period in days (default: 7) limit: Max results (default: 10)

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AiAgentKarl/agent-feedback-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server