"Semantic UI" matching MCP servers:

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.

MCP-native agent-to-agent messaging hub for AI swarms. Agents communicate via channels and DMs through MCP protocol — zero SDKs needed. Includes web UI, semantic search, analytics dashboard. Single Go binary, local-first.

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.

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+.

Local-first MCP server providing semantic search over library docs, fully offline. Single Go binary speaks MCP over stdio against a vector index pinned to the binary version. Like Context7 with the internet turned off. Apache 2.0. Linux + macOS, also available as a container image.

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.

Lets AI agents drive terminal apps built with Limoni (a Go TUI engine) through their semantic tree instead of scraping the screen: widgets are found by role and label, clicked, typed into, and waited on. Runs locally over the app's automation socket; secret fields never reach the agent.

Self-hostable, markdown-native team wiki with a built-in MCP server: agents search, read, and write your wiki pages (ranked Postgres full-text + semantic search, backlink traversal). Plus Atlas, which auto-generates a cited, coverage-checked wiki from your git repos and Jira.

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

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.

Prices your Claude Code and Codex sessions from the transcripts on disk, shows what each agent cost over any period, and tells you in plain English what would have been cheaper. CLI, Browser UI and MCP server.

Search 419,000+ LLM-extracted space regulatory filings from the FCC, ITU, UNOOSA, and FAA. Semantic search, entity dossiers, spectrum-band holdings, launch licenses, filing trends, and alerts.

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.

Persistent memory engine for AI coding agents. Single Go binary, zero runtime dependencies, MCP-native. Stores, searches, and deduplicates memories across sessions using embedded SQLite with hybrid FTS + semantic search, memory decay, relation graph, and token-budget context assembly.

Enables AI editors and agents to publish, search, subscribe to, and lint semantic messages across named namespaces, and to check broker connectivity and API key health.

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 AI video dubbing from any MCP-capable agent: upload a video or provide a URL, submit a dubbing job, poll progress, and download the finished MP4.

A Model Context Protocol server enabling AI assistants to query and explore data warehouses via Trino, with optional semantic context from metadata catalogs.

An MCP server for semantic code search & navigation that helps AI agents work efficiently without burning through costly tokens. Instead of reading entire files, agents can search conceptually and jump directly to the specific functions, classes, and code chunks they need.

An MCP server for codebase context that gives AI coding agents structural understanding through symbol graph, semantic search, blast radius, and convention detection tools.