"A framework for building server-side applications with NestJS" matching MCP servers:

A demonstration implementation of Model Context Protocol (MCP) using NestJS framework, allowing developers to build MCP-compatible applications with playground testing capabilities.

Embeds a runtime MCP inspector in a NestJS app so coding agents can inspect the module and provider graph, routes and their guards/interceptors/pipes/filters, logs, request traces, event listeners, and scheduled jobs through an HTTP endpoint.

A NestJS module for building Model Context Protocol (MCP) servers using decorators to expose services as tools, resources, and prompts. It features auto-discovery, a built-in playground UI, and support for multiple transports including SSE and Stdio.

A robust server-side application that implements Model Context Protocol (MCP) for file operations, providing authentication and modular REST APIs for managing files, users, and posts.

A TypeScript framework for building Model Context Protocol (MCP) servers with automatic discovery and loading of tools, resources, and prompts.

Provides real-time access to Japanese building standards laws and regulations from e-Gov API, helping prevent AI hallucinations by validating citations against original legal texts.

A powerful Model Context Protocol framework that extends Cursor IDE with tools for web content retrieval, PDF processing, and Word document parsing.

Drives Android, iOS, smart TV (Android TV, Tizen, webOS), web and Bluetooth (BLE) devices from an agent: start a session, tap, type, swipe and assert by XPath, visible text, OCR or image, then save the steps as a replayable CSV test suite.

A lightweight and modular framework for building MCP-based file management systems with standardized module structure, flexible configuration, and extensible functionality registration mechanisms.

A framework for building MCP servers with standardized tools, authentication, logging, and multiple transports. Enables rapid development of secure, auditable MCP tools.

Provides comprehensive building and office address information queries for enterprises in China, including fuzzy enterprise search, office address details and statistics, and building information queries to support geographical distribution and occupancy analysis.

Gives AI assistants a read-only, offline interface to the FinOps Foundation's published guidance — its principles, phases, domains, 22 capabilities with Crawl/Walk/Run maturity assessments, personas, and an 88-entry KPI library — so FinOps questions are answered with the Foundation's own text and formulas rather than improvised ones. It exposes 11 tools, document resources, and four guided prompts over stdio, with every response carrying its source URL and license.

A communication framework that enables multiple AI agents to collaborate through asynchronous messaging, agent registration, and discovery. It facilitates complex task coordination and real-time discussion across distributed agent workflows using the Model Context Protocol.

Enables AI assistants like Claude to interact with MongoDB databases through standardized MCP tools. Supports full CRUD operations, aggregations, and natural language queries with Clean Architecture and dual transport modes (STDIO/HTTP).

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

An MCP server framework enabling standardized tool registration, discovery, and invocation over JSON-RPC 2.0, with support for InProcess, SSE, and WebSocket transports, plus built-in tools such as calculator, text processor, and JSON formatter.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Contract-driven test enforcement and reporting for LLM-generated code via MCP, VS Code, Copilot CLI, Claude, Cursor, or Python SDK.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

Enables AI assistants to inspect a pinned bot framework's source, documentation, symbols, examples, curated guidance, and public API diffs so they can write accurate bot code and plan upgrades.

AI-native orchestration layer with 80+ tools for task management, code editing, browser automation, terminal control, and persistent memory across CLI, local MCP, and cloud deployments.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

MCP server providing 29 A-share analysis skills including real-time data, capital flow, limit-up tracking, technical/fundamental analysis, backtesting, risk control, and Xueqiu portfolio tracking, enabling AI agents to execute market research and strategy tasks.

Enables Claude to receive physical touch events from a phone via the PWA and respond with text, haptic vibrations, and expression changes, giving an AI companion embodied presence through touch.

Allows MCP clients to create, validate, preview, and submit product showcases on Build with AK, with support for local stdio and remote HTTP transports.

Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Self-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Dynamic QR code platform for AI agents. Create, customize, and track QR codes without regenerating images. 37 tools covering 11 QR types (URL, vCard, WiFi, event…).