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

Exposes MCP tools that let an agent search a catalog, inspect a paid service's pricing, fetch it with payment handled automatically, and check its remaining budget and active spending limits. Payments are authorized against a signed mandate from the owner, so agents can buy API access over HTTP 402 without ever holding the owner's private key.

Lets Codex inspect a live macOS AppKit interface through a debug-only bridge, without Accessibility or Screen Recording permissions, and maps clicks to NSViews with hierarchy and geometry details.

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

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

MCP server that serves agent skills (SKILL.md bundles) to any MCP client, exposing them via tools and resources for tool-oriented and resource-aware clients.

Exposes TELOS governance primitives—action scoring, receipt verification, Purpose Anchor inspection, audit-chain queries, and CCRS counterfactual replay—as MCP tools, resources, and prompts for any MCP-compatible client.

An intelligent MCP server that enables seamless restarting of Claude's MCP handler process without disrupting the UI, allowing for plugin reloading without closing the entire Claude Desktop application.

A strategic advisory agent that applies Clayton Christensen's frameworks, such as Jobs-to-Be-Done and Disruption Theory, to analyze business decisions. It enables users to evaluate organizational capabilities, explore historical case studies, and receive theory-grounded strategic insights.

Description: Persistent memory for AI agents with rollback, audit trails, semantic search, and knowledge graph. Zero-config local SQLite or cloud API. 23 tools, 6 resources, 3 prompts.

An MCP server that exposes the Agent Skill creation guide (9 phases) as MCP resources, enabling AI agents to build SKILL.md files on demand.

Integrates Agent Skills into LLMs by discovering skills in a configured directory and progressively loading their instructions and resources on demand through a structured disclosure pattern.

Enables Claude Code to delegate autonomous web browsing, deep research, and multi-tab management to a Comet browser session, with tools for asking questions, capturing screenshots, managing tabs, switching modes, and uploading files.

Gives AI agents a smart-contract wallet on Base (USDC) with 10 stdio tools: create wallets, send USDC payments, pay x402-protected HTTP resources, and run ERC-8183 escrow Jobs for A2A service delivery.

A starter project for rapidly developing Model Context Protocol (MCP) servers using the TypeScript SDK and Zod schema validation. It includes example implementations for tools and resources to streamline the creation of custom MCP integrations.

A proxy server that connects MCP clients to the Zihin.ai platform via HTTP, enabling management of AI agents, LLM models, and configuration templates. It provides tools for agent creation and resources for discovering tenant-specific agents and schema templates.

MCP server that enables AI agents to make autonomous Bitcoin Lightning Network payments using the L402 protocol. Agents can pay for API access, purchase resources, and complete transactions without human intervention — invoice comes in, sats go out, done.

Exposes the Agentic Patterns Catalog as MCP resources and tools for AI coding agents to search, retrieve, and recommend patterns, recipes, frameworks, methodologies, and anti-patterns.

An MCP (Model Context Protocol) server that integrates with the ArgoCD API, enabling AI assistants and large language models to manage ArgoCD applications and resources through natural language interactions.

Enables learning how to build and use an MCP server with tools, resources, and prompts through a Python example.