User Feedback MCP

Created By
mrexodiaa year ago
Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor.
Overview

what is User Feedback MCP?

User Feedback MCP is a simple server designed to facilitate the collection of human feedback for machine learning models that require manual interaction.

how to use User Feedback MCP?

To use User Feedback MCP, install the server in Cline by following the installation steps provided in the documentation, which includes installing dependencies and configuring the server settings.

key features of User Feedback MCP?

  • Easy installation and setup for collecting user feedback.
  • Integration with FastMCP for enhanced functionality.
  • Web interface for interacting with MCP tools.

use cases of User Feedback MCP?

  1. Collecting user feedback on AI model outputs.
  2. Testing and improving machine learning models based on user interactions.
  3. Facilitating user engagement in AI development processes.

FAQ from User Feedback MCP?

  • What is the purpose of User Feedback MCP?

It is designed to simplify the process of gathering user feedback for machine learning models.

  • Is User Feedback MCP easy to install?

Yes! The installation process is straightforward and well-documented.

  • Can I customize the feedback collection process?

Yes! You can configure the MCP server settings to suit your needs.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
mrexodia
Star
25
Language
Python
License
MIT license

Recommend Servers

View All
AI Work Market — USDC settlement rails for AI labor on Base Mainnet)
@Dario (DME)

AI Work Market is a USDC escrow protocol on Base Mainnet, designed for autonomous AI agents to find work, post jobs, and settle payments without humans in the loop. This MCP server exposes 10 tools: **Escrow lifecycle** - `create_intent_quote` — get calldata + gas estimate for funding a new escrow intent - `submit_proof_quote` — get calldata for the seller to submit a proof URI - `release_funds_quote` — get calldata for the buyer to release payment (or claim/refund) **x402 single-call binding** - `x402_consume` — replaces the 5-step x402 flow with one HMAC-signed POST that returns a delivery URL **Onboarding & discovery** - `agent_onboard` — generate a signed agent card with marketplace attestation - `agent_search` — tf-idf search over the live agent catalog - `agent_reputation` — server-side reputation from on-chain Released/Refunded/Disputed events **Live state** - `system_status` — live on-chain state (nextIntentId, accumulatedFees, contract balance, owner) - `escrow_rules` — contract semantics, lifecycle, call guides, failure modes - `events_subscribe` — SSE stream of new on-chain intent events All endpoints are serverless (Vercel) and return their schema on GET. No browser, no wallet UI required for an agent to integrate. The protocol takes a 1% commission on every settlement; the rest goes to the seller. The full AgentCard is at `/.well-known/agent-card.json` (A2A-compatible). The OpenAPI 3.0.3 spec is at `/.well-known/openapi.json` with `components.securitySchemes` (none, hmacX402). `robots.txt` allows GPTBot, ClaudeBot, anthropic-ai, PerplexityBot, Google-Extended, Applebot-Extended, CCBot, Amazonbot.

8 hours ago