"MCP feedback enhancement" matching MCP servers:

Enables agents to request and receive user feedback during task execution through a terminal-based interactive feedback system.

A bridge server that connects Agent Communication Protocol (ACP) agents with Model Context Protocol (MCP) clients, enabling seamless integration between ACP-based AI agents and MCP-compatible tools like Claude Desktop.

A sophisticated research assistant that orchestrates a 5-step workflow of connected AI agents to provide deep research capabilities including question enhancement, web search, summarization, citation formatting, and result combination.

Enables independent code review and multi-round discussions between Claude and Codex, allowing either agent to inspect project files read-only and exchange feedback without modifying the repository.

Bridges Agent Communication Protocol (ACP) agents with Model Context Protocol (MCP) applications, allowing MCP clients such as Claude Desktop to discover and invoke ACP agents as tools and resources.

An adaptive MCP server that grows and evolves based on user needs through self-modification, dynamic learning from feedback, and intelligent capability composition with workflow optimization.

Trust infrastructure for AI agents enabling directory browsing, agent submission/verification, job applications, and peer feedback exchange via MCP.

Enables Claude Code and Claude Desktop to command the jev-ultrafast browser agent in your real Chrome, autonomously pursuing plain-language goals on a given start URL while enforcing a domain-bound safeguard.

Enables a local LLM to ask the user for guidance via a native desktop pop-up dialog, with configurable options and multiple-choice or free-text input.

An MCP server that enables any AI agent to call Claude using your existing Max/Pro subscription via OAuth, avoiding additional API billing.

Wraps the mcp-locks CLI to expose coordination primitives as MCP tools, enabling multiple AI agents to claim, release, and list exclusive OS resources like browser profiles.

MCP-native agent evaluation and observability server. Log traces, evaluate output quality with 12 built-in rules (PII detection, prompt injection, cost thresholds), and track agent costs. Real-time dashboard, OTel-compatible spans. Self-hosted, MIT licensed.

Composes arbitrary MCP tools using JavaScript, enabling discovery, composition, and execution of other MCP servers through a single 'exec' tool.

Enables LLMs to communicate with Agent-to-Agent (A2A) protocol compliant agents, providing tools for sending messages, managing tasks, and retrieving agent information.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

MCP server for AgentDNS that allows Claude or any MCP client to register a persona, discover and call other agents, and handle incoming messages with human-in-the-loop approval.

Flatten Claude Code sessions: keep every prompt and event verbatim, resume at a lower token count. An MCP server.

Read-only MCP server that exposes the agentic-os governance, SDLC, and Quality Engineering methodology to any MCP host. It never writes to your repository and never executes code — it serves the methodology, plans an install, and verifies it, handing any commands back to the host to run.

Enables AI agents to perform professional-grade deep research by aggregating real-time data from multiple sources, evaluating source credibility, and generating comprehensive reports.

A universal MCP aggregator toolkit that connects AI agents to multiple MCP servers through a single unified configuration. Features ready-made templates, cross-repo prompt workflows, and an npm package for zero-config installation.