MCP Search Server with Feedback-Driven Ranking for Claude Desktop

An MCP (Model Context Protocol) search server has been built for Claude Desktop that implements feedback-driven ranking. The server runs two search engines—Exa and Tavily—in parallel, and no API key is required for use.
Setup and Configuration
To add this server to your Claude Desktop configuration, use the following JSON snippet:
{
"mcpServers": {
"meyhem": {
"command": "npx",
"args": ["mcp-remote", "https://api.rhdxm.com/mcp/"]
}
}
}
Tool Workflow
The server provides three tools that follow a specific sequence:
search→select→outcome
After using a search result, users report whether it worked via the outcome tool. This feedback signal is then fed back into the ranking algorithm, causing URLs that help agents succeed to rise in priority for all users. The system is designed to improve as more people use it.
The server is accessible at https://api.rhdxm.com and was shared on the r/ClaudeAI subreddit by user /u/Dashcamvideo.
📖 Read the full source: r/ClaudeAI
👀 See Also

OpenClaw Agent Relay Plugin Fixes Telegram Delivery in Multi-Agent Setups
The openclaw-agent-relay plugin addresses the persistent issue where sessions_send responses go to webchat instead of Telegram by using gateway WebSocket RPC to trigger agent turns with deliver:true, eliminating the need for workarounds like explicit message tools or announce steps.

Qwen 3.6 27B hits 2.5x speed with MTP speculative decoding on llama.cpp
A Reddit user reports 2.5x faster inference on Qwen 3.6 27B using MTP speculative decoding with a custom llama.cpp PR, achieving 28 tok/s on Mac M2 Max 96GB. Includes pre-converted GGUF quants and fixed chat templates.

Be brief beats caveman plugin in Claude Code compression benchmark
A 24-prompt benchmark shows Claude Code's caveman compression plugin produces the same token counts and quality as simply prepending 'be brief.' — but the plugin's consistent output shape and safety escape rules offer structural advantages.

SOPHIA Meta-Agent for AI Agent Maintenance
SOPHIA is a meta-agent designed as a Chief Learning Officer that observes, diagnoses, researches, and proposes improvements to other AI agents in production ecosystems. The system was designed through 7 iterations using 4 frontier models with human approval required for all deployments.