Packages

MCP server for Google Sheets - read, write, and query spreadsheet data

Honeybadger MCP server providing an MCP interface (via stdio/docker) to access Honeybadger API data and actions such as projects, faults, notices, and insights. Defaults to read-only mode to prevent write/destructive operations unless explicitly enabled.

MCP Server for WHO ICF (International Classification of Functioning) on Cloudflare Workers

Official MCP server for Linkly - Create and manage short links, track clicks, and automate URL management

Lumen is a local semantic code search engine for AI coding agents. It indexes a local codebase into semantic chunks (via AST/tree-sitter), embeds them using locally hosted embedding backends (e.g., Ollama/LM Studio), stores vectors in SQLite with sqlite-vec, and exposes an MCP tool (semantic_search) so agents can retrieve relevant code without reading entire files.

Reference servers that demo how authentication works with the current [Model Context Protocol spec](https://spec.modelcontextprotocol.io/specification/2025-03-26/basic/authorization/).

An MCP (Model Context Protocol) server that lets AI assistants query and manage Moneybird bookkeeping data (contacts, invoices, accounts, products/projects, time entries) and optionally make custom Moneybird API requests, using a Moneybird API token provided via environment variables.

<!-- mcp-name: io.github.aahl/mcp-notify -->

novyx-mcp provides a Model Context Protocol (MCP) server for persistent agent memory. It supports local operation using SQLite for core memory actions, and can connect to Novyx Cloud for an expanded feature set including audit/rollback, knowledge graph, shared context spaces, replay/tracing, evaluation, and governed/autodefense/threat-intel-related tools (depending on plan).

**Persistent memory for AI agents.** Store decisions, preferences, and context that survive across sessions. Build knowledge graphs that compound over time. Works with Claude, Cursor, Windsurf, Gemini CLI, and any MCP-compatible tool.

A lightweight, embedded Go rule engine framework that orchestrates business logic through configurable DAG-based rule chains, supporting hot-reload, heterogeneous data source integration, and zero external middleware dependencies.

An MCP server that exposes a directory of “Claude Skills” (SKILL.md plus scripts and references) to any MCP-capable AI agent. It provides tools to list skills, load skill instructions/resources, execute bundled skill scripts in a sandboxed environment, and read/write/edit files within a configured workspace.

**Search Twitter, Instagram, Reddit & TikTok from any AI agent.** 1.5B+ posts indexed. Natural language queries. CSV exports up to 500K rows. No API keys needed.


trading-mcp is a TypeScript MCP server that exposes tools for stock screening, fundamental metrics, insider trading analysis, options put/call sentiment, and news/social sentiment analysis (via OpenAI and Reddit when configured).

Social MCP server — DMs, presence, and discovery for AI-assisted developers. Works with Claude Code, Cursor, VS Code, Windsurf, and any MCP client.

BoltMCP is an enterprise-grade MCP orchestration platform to create, deploy, and manage custom MCP servers on-premises.

winremote-mcp runs a Windows “Model Context Protocol” (MCP) server on a Windows machine to enable remote desktop automation and administration for MCP-capable agents/clients (e.g., Claude Desktop, OpenClaw). It provides tools for screenshots, GUI input automation, PowerShell/shell command execution, file operations, system/process management, OCR, and screen recording. It supports API-key bearer auth, IP allowlisting, TLS, and an embedded OAuth 2.0 authorization server.

Provides a local MCP (Model Context Protocol) server that exposes DaisyUI component documentation as MCP tools. It can fetch DaisyUI’s public `llms.txt` and store component docs as local Markdown, then serve two tools: list components and get component documentation.

FastMCP is a Python framework for building MCP (Model Context Protocol) servers (exposing tools/resources/prompts) and connecting to MCP servers with clients. It focuses on turning Python functions into MCP tools with automatic schema/validation/documentation generation, and handling MCP transport/authentication/lifecycle details for you.