"Glama AI MCP Inspector - DataNexus MCP Server Resources Tab" matching MCP servers:

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

An MCP server for searching and exploring MCP servers from the Glama MCP directory. This server provides tools to search for MCP servers, get detailed information about specific servers, and explore available server attributes using the Glama MCP API.

Enables MCP clients to access the Glama AI gateway through tools for listing models, chat completions, streaming completions, and request status checks using a single API key.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

MCP server that inspects Git repository changes, runs optional validation commands, and generates Markdown reports. Exposes a review_repository tool for AI clients to analyze repositories.

Enables AI clients to inspect Git repository changes, run allowlisted validation commands, and generate Markdown review reports via MCP, with validation disabled by default for security.

A basic MCP server template that provides a foundation for building custom tools, resources, and prompts. Serves as a starting point for developers to create their own MCP server functionality.

MCP server for the Ghost Inspector API that lets agents inspect and manage end-to-end browser tests, offering read-only tools for inventory, module usage, and stale test analysis, plus opt-in guarded write operations.

MCP server that allows reading inside Java archives (classes, APIs, sources, resources, bytecode) without extraction, with focused tools to minimize context window noise.

Decompiles Maven dependencies into readable Java source directly inside your AI agent.

Enables LLMs to inspect and test other MCP servers by listing and calling their tools, reading resources, and getting prompts. Supports stdio, SSE, and HTTP transports for both local and remote MCP server inspection.

Enables AI agents to audit KiCad PCB designs through deterministic DRC/ERC checks, spatial heuristics, and multimodal vision review, returning structured, prioritized findings with coordinates and fix guidance.

A Node.js debugger for AI agents that enables setting breakpoints, stepping through code, and inspecting variables via the Chrome DevTools Protocol.

Provides programmatic access to MCP server testing, debugging, and validation capabilities by wrapping the official MCP Inspector. Enables users to test tools, validate protocol compliance, discover server capabilities, and debug MCP servers through natural language interactions.

Exposes Django runtime information (settings, apps, URLs, models, migrations) as MCP resources for AI agents to inspect a live Django project without static analysis.

Enables AI agents to drive a headless browser to a Storybook story and capture every custom event a component dispatches with zero registration, while flagging shared, retargeted, undocumented, and not-composed events. It also lets agents dispatch synthetic events at the rendered component to verify it responds as documented.

Gives AI coding tools access to the CSS cascade the way DevTools does — which rules matched, which won, where each came from.

An MCP server that lets an agent inspect and operate Redis-backed job queues, supporting Asynq and BullMQ backends with per-state counts, job details, and state transitions.

Enables LLMs to inspect a live BabylonJS scene through structured scene data, WebGL frame captures, screenshots, and arbitrary scene evaluation, with optional Gemini vision analysis.

Inspects and queries SQLite databases on Android devices via ADB, supporting listing databases/tables, describing schemas, and executing SELECT/INSERT/UPDATE/DELETE queries.