"AWS instance metadata service endpoint URL" matching MCP servers:

MCP server for AI Diagram Maker — generate software engineering diagrams from natural language, code, ASCII diagram, images, or Mermaid. Inline diagram rendering using MCP apps UI and diagram URL in responses. Works with Cursor, Claude Desktop, Claude Code, and any MCP-compatible AI.

A FastMCP server that turns JSON data into Plotly figures, deployable as an isolated service on Modal. Data goes in as JSON; a validated Plotly figure (JSON) or a rendered PNG comes back over the Model Context Protocol.

Enables querying Tableau lineage through the Metadata API via MCP, supporting impact analysis, where-used lookups, and content search. Provides read-only tools for answering natural-language questions about workbooks, datasources, fields, and dependencies.

A Python MCP server for Metabase that enables AI assistants to query databases, manage dashboards, and interact with your Metabase instance.

diagramzu-mcp lets an AI client (Claude, Cursor, ChatGPT, etc.) author Mermaid diagrams in a shared workspace that a team can read, comment on, embed, and present at a clean URL — rather than just generating a one-off diagram. Hosted endpoint https://mcp.diagramzu.ai/mcp or local npx -y @diagramzu/mcp. Also listed in the official MCP registry as ai.diagramzu/mcp.

Enables natural language interactions with Salesforce data, metadata, and reports, including report creation, discovery, and schema inspection.

An MCP server that enables LLMs to create and open diagrams in draw.io using XML, Mermaid, or CSV formats, by building a URL with compressed content and opening it in the browser.

MCP server exposing BI Portal's self-service Report Builder to MCP clients, enabling listing datasets, running ad-hoc queries, creating/editing/submitting draft reports, and viewing saved dashboards.

A Model Context Protocol (MCP) server for Tableau Server. Enables AI assistants to interact with Tableau workbooks, views, datasources, and metadata.

Enables AI agents to automatically analyze AWS LNA CSV data and generate competency assessment PPT reports with radar charts and team-level insights.

MCP server enabling AI agents to directly query and manage Power BI datasets, reports, and workspaces via DAX, with built-in data security policies and support for both Power BI Desktop and Service.

Enables an MCP client to drive a running SDR++ instance to discover, analyze, identify, demodulate, record, decode, and log radio signals.

Enables natural-language querying of databases via SQLBot, with datasource discovery, metadata inspection, and report generation.

Enables natural language interaction with AWS QuickSight for building, editing, and managing analyses, datasets, and dashboards, including chart creation, SQL updates, and QA verification.

Enables AI clients to generate over 26 chart types via MCP, automatically starting a private rendering service.

Enables AI assistants to create, edit, and export IFC5/IFCX building information models through natural language, handling spatial structure, elements, geometry, metadata, validation, and export.

Enables an AI assistant to inspect GDSII layouts and stackup files, validate model scripts without running them, and generate AWS Palace models locally, along with layout previews, gmsh visualisation, S-parameter summaries, and inductor/capacitor value extraction. It works on files in the user's own Python environment and disk, without invoking the Palace solver.

Enables Claude Code and other processes to control the lys interactive multi-dimensional data analysis and visualization platform by executing Python commands in it and viewing the resulting lys and matplotlib graphs. It connects over a local socket or TCP to a lys instance running in remote mode.

An MCP server that lets an AI assistant drive Epistemic Network Analysis models hosted on the webENA cloud service, enabling project listing, model running, and result visualization.

Metabase includes a built-in Model Context Protocol (MCP) server that lets AI clients connect directly to a Metabase instance. It uses the Streamable HTTP transport and builds on Metabase's Agent API to expose tools for searching, exploring, querying, and visualizing data — all scoped to the connecting user's permissions.