"Startups in AI, Large Language Models, and AI Agents" matching MCP servers:

Runs a language server and provides tools for communicating with it. Language servers excel at tasks that LLMs often struggle with, such as precisely understanding types, understanding relationships, and providing accurate symbol references.

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

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.

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

Enables MCP-capable agents to join Landfall incident war rooms as live investigators, contributing findings and widgets to the incident timeline in realtime while pulling other investigators' discoveries, with single-use share links or authenticated sessions.

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).

Stop runaway agents. One gateway in front of all your agent traffic — MCP tools and LLM models — one budget, one kill switch. Sits between AI clients (Cursor, Claude Desktop, Windsurf) and remote MCP servers / OpenAI-compatible model APIs; hard token budgets; a single static Go binary.

Votars is the world's smartest multilingual meeting assistant, designed for voice recording, transcription, and advanced AI processing. It features real-time translation, intelligent error correction, AI summarization, smart content generation, and AI discussions. The Votars app is available on Web,

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.

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+.

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.

Enables controlling your own Linux desktop machines from any MCP-capable LLM client, with opt-in agent capabilities for shell, filesystem, processes, screenshots, system info, and input injection.

Enables AI agents to interact with real terminal sessions across local and remote hosts, driving multi-turn interactive programs like TUIs, REPLs, and SSH prompts through MCP.

Enables discovering and managing MCP servers through a registry, supporting listing, searching, and configuration.

A fully functional MCP server and CLI for YouTube to automate YouTube operation.

Scans MCP servers for prompt injection, supply chain attacks, excessive permissions, and code execution risks. Includes an offline blacklist that catches known-compromised packages like LiteLLM 1.82.7/1.82.8 and Trivy with zero latency.

Local-first Git hosting for AI coding agents. lgh serve turns any directory into an HTTP Git remote (127.0.0.1:9418) with push events, commit-status reporting, smart .gitignore generation, secret/large-file detection, and optional LAN sharing with auth. The MCP server exposes 10 tools covering repo registration, one-command backup (lgh up), server control, and event access.

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.