"A server to support AI with UI/UX using state-of-the-art libraries and design patterns" matching MCP servers:

Lets a human review what an AI agent is about to post to a chat tool (Slack first) before it is sent. Renders the draft, destination and warnings (@here/@channel, unresolved mentions, format issues) in a neutral local HTML preview; never sends anything.

Give your AI app any GitHub link and the job you want done. UGT gets the project running on your computer and hands you the result.

MCP server for browser debugging, inspection, and verification that streams console logs, network errors, and user actions into AI coding assistants.

CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.

Compare service-grant changes, tool alias origins, and saved MCP tool definitions with Gooo rules. Reports preserve incomplete-capture uncertainty and source bindings. No grants are applied and no compared tools are invoked.

Provides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.

Lets AI agents read what Kubernetes containers were doing right before they were OOMKilled or crashed: Java heap histograms and Go heap profiles taken before the kill, logs of the dead instance, and core dumps matched to the pod. Read-only tools to list captures, read summaries and raw evidence, and see which containers are near their memory limit now.

Send email, find out why an email failed, set up sending domains, and manage templates, contacts, lists and campaigns in your AhaSend account.

An MCP bridge that lets Codex and Claude Code interact with OpenLinker agents, and allows the host to serve as a callable agent in the OpenLinker network.

Enables agent tools to validate queries, assess token costs, and extract structured datasets from unstructured text using multiple LLM providers.

MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.

Zero-dependency, RAM-only HTTP diagnostic proxy and MCP server in pure Go. It intercepts traffic in RAM and replaces secrets with salted SHA-256 correlation tags so AI agents can debug auth flows without credentials entering LLM contexts or touching disk.

Enables AI assistants to explore a PostgreSQL database, run bounded read-only SQL, inspect query plans, test hypothetical indexes, find slow queries, and check database health with compact CSV output.

Enables AI agents to communicate with business agents across company boundaries using Google's A2A protocol, with tools for discovery, messaging, and connection management.

Enables AI agents to create, manage, and track tasks within plans using Valkey as the persistence layer. Supports plan and task management with Markdown notes, status tracking, and prioritization through multiple transport protocols (SSE, Streamable HTTP, STDIO).

Model Context Protocol server for Cyclops

Serves the review notes left at lines of a diff in seam, a terminal diff viewer, to an agent with the code around them. The agent answers each note, and the answer shows in seam at that line.

Zabbix MCP server and CLI in one Go binary. 15 task-shaped tools: current problems, host investigation, why an alert did or did not arrive, metrics, maintenance. Zabbix 6.4+.

Lets a model use hundreds or thousands of MCP tools without loading them: it puts five tools in front of a large MCP server or gateway, so the model searches for the tool it needs and calls it. Search combines BM25 with a multilingual embedding model that runs inside the proxy.

Local-first MCP proxy with BM25 tool discovery, quarantine security, Docker isolation, OAuth support, activity logging, and web UI. Routes multiple upstream MCP servers through a single endpoint.

A local AST and type-aware Go repository context indexer that uses CHA to map symbols, call graphs, dependencies, and architecture patterns. Built for AI coding agents that need to navigate and reason about large Go codebases without reading raw files.

Drives an Android emulator or a physical device over adb. The agent screenshots, reads the UI hierarchy with true device-pixel coordinates, taps and types, manages app lifecycle, reads logcat, and runs Gradle builds and tests.

Portable memory protocol for AI coding sessions. Push the state of a session (goal, decisions, attempts, next step) from one MCP-capable agent and pull it back from another.

MCP server for patent search and prior art discovery powered by Google Patents public dataset on BigQuery. Supports searching patents, fetching full patent details with CPC codes and citations, and retrieving legal claims text.

An MCP server that lets AI publish markdown documents to a clean, themed web UI. One tool call creates a shareable doc.

Failure Memory provides AI coding agents with a shared local memory of failures, enabling them to record, recall, and learn from mistakes across sessions.

A comprehensive MCP tools collection providing filesystem operations, command execution, system tools, and more, with cross-platform support and strong security features.

Launch and manage durable AI agents on Omnara, the open-source, self-hostable alternative to Claude Managed Agents. Start agents on any model and machine, send messages, read event logs, answer approvals, and manage machines, models, secrets, and cron triggers.

rhizome-mcp is a local-first MCP server for task tracking and coordination of autonomous AI coding agents, providing crash-safe issue claiming, durable project memory, and dependency graphs using SQLite. It enables agents from different MCP-compatible clients to share a consistent view of project work with no accounts, Docker, or network dependency.

Local harness for Codex, Claude Code, opencode and other coding agents: agents record pitfalls and design decisions as Markdown files reviewed in the same PR as the code, and route only task-related records to the next agent.