"DataNexus MCP Inspector - Resources Tab" matching MCP servers:

A Model Context Protocol (MCP) server for validating Mermaid diagram syntax and providing comprehensive grammar checking capabilities

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.

Provides local, offline searchable access to Roku and BrightScript development documentation via MCP tools and resources, including full-text search, sectioned reading of large docs, and background syncing from the upstream repo.

Provides read-only access to the ProPaths verified protein interactome, letting AI agents search proteins, retrieve mechanistic interaction details, and explore pathway ontology through MCP tools, resources, and prompts.

mistral-mcp is a TypeScript MCP server (spec 2025-11-25) that exposes the full Mistral AI API surface: 22 tools: chat, OCR, audio (Voxtral), vision, agents, embeddings, moderation, classification, files, batch, sampling, FIM (Codestral), streaming 2 resources: mistral://models, mistral://voices 6 curated prompts (French + English) with MCP argument completion Dual transport: stdio (default) + Str

A task-board MCP server that provides tools to search, create, and update tasks, resources for reading the board, and prompts for standup and triage workflows.

Provides a Model Context Protocol server with tools for knowledge base search, retrieval, and addition, plus system time, resources, and prompts. Supports stdio and Streamable HTTP transports for local and shared deployments.

Enables Claude and ChatGPT to help users pick UC Irvine classes by searching live course sections, comparing grade distributions by instructor, checking prerequisites and AP credit, and detecting schedule conflicts, all through tools, guided prompts, and reference resources.

Exposes Cursor-style skill packs (SKILL.md trees) via MCP resources, tools, and prompts, enabling any MCP client to list, get, search skills, and retrieve skill context.

A production-grade TypeScript starter for building Model Context Protocol servers, supporting stdio and Streamable HTTP transports with modular tools, resources, and prompts.

A production-grade MCP server that provides real-time weather data and demonstrates the complete MCP protocol surface including tools, resources, prompts, and structured output.

An MCP server that demonstrates the Model Context Protocol using a mock SQLite database of an online store, offering tools for product search, sales analysis, and reviews, along with resources and prompts for learning MCP integration.

A Know Your Business workbench that searches French company registry data, manages review dossiers, and exposes tools, resources, prompts, completions, elicitation, and sampling to any MCP client.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

Enables sending web push notifications and managing Pushpad resources (notifications, subscriptions, projects, and senders) through natural language, using the Pushpad API.

Provides access to Deutsche Bahn train timetables, station information, and schedule changes through Model Context Protocol tools and resources.

A CLI-based Model Context Protocol server that exposes PubNub SDK documentation and Functions resources to LLM-powered tools like Cursor IDE, enabling users to fetch documentation and interact with PubNub channels via natural language prompts.

A production-grade, extensible Python template for building Model Context Protocol servers with support for Streamable HTTP and stdio transports. It provides a structured framework for implementing tools, resources, and prompts with built-in authentication, observability, and background task management.

A Model Context Protocol server for interacting with MongoDB Databases and MongoDB Atlas. It enables AI assistants to query, manage, and operate on MongoDB data and Atlas resources through natural language.