"An overview of end-to-end testing" matching MCP servers:

Publishes a spending-summary tool alongside an interactive HTML view, letting people click a category in the answer to fetch the individual expense records behind that total. Keeps calculations and their supporting evidence together in a single inspectable flow.

Enables discovery of Fabric/Power BI workspaces and semantic models, execution of DAX queries, and generation of executive HTML reports with visualizations.

Enables an agent to turn a paper's draft into editable Figma frames for publication-ready figures, checking every number against the paper and verifying the exported PDF.

MCP server that wraps Nightjar's analytics API, enabling Claude Code to query events, funnels, dashboards, and metrics through natural language.

Enables AI agents to work end-to-end with Power BI and Fabric through 26 high-level tools that orchestrate specialized engines for semantic modeling, report authoring, cloud operations, validation, and visualization UX.

Provides 102 tools for end-to-end data science pipelines, enabling data loading, cleaning, visualization, modeling, and reporting via natural language.

Enables AI agents to drive OpenFOAM end to end: cloning tutorials or custom cases, editing dictionaries, meshing and running solvers in the background, tracking convergence and job status, and analyzing results. It also renders flow images — slices, patches, streamlines, iso-surfaces and residual or force plots — back to the agent.

Enables an AI assistant to build Power BI projects end to end: data modeling (tables, DAX measures, relationships, calculation groups, roles, field parameters) against an open Power BI Desktop via TOM/XMLA, and reports (pages, visuals, formatting, bookmarks, themes) as PBIR files in a .pbip project. Every visual is cross-checked against the real model before being written, so generated dashboards don't break on open.

MCP server providing data analytics tools for AI agents to load, clean, analyze data, generate charts and dashboards.

Enables end-to-end analysis of Reddit discussions: fetches posts, performs sentiment and toxicity detection, generates visualizations and word clouds, and optionally builds Neo4j knowledge graphs, all through natural language orchestration.

Enables rendering, validation, formatting, and inspection of D2 diagrams via the Model Context Protocol, using WASM for rendering without requiring the d2 binary.

Enables agents to turn structured data into production-ready static maps, returning rendered PNG and SVG URLs along with an editable map link.

Enables turning data into map images of countries, states, provinces, counties, continents, and the world, including choropleths, category maps, and pinned locations.

A Model Context Protocol server that gives an LLM a structured visual layer to describe what exists and get back a clean, precise SVG diagram instead of ASCII art.

A demo MCP server that returns an interactive dashboard (bar chart with dataset selector) as an MCP App via the official MCP Apps extension (SEP-1865).

Enables converting ASCII and Unicode text diagrams into crisp, animated SVG with 1:1 verification, including repair of misaligned diagrams.

An MCP server that extracts energy-usage charts from utility-bill PDFs, returning structured time-series data and annotated images.

MCP server for generating diagrams, charts, and visualizations using Gemini image generation on Vertex AI. Supports auto-detection of diagram types, multiple style modes, and iterative refinement.

An MCP server that enables AI agents to compile, refine, and interlink knowledge into a persistent wiki, replacing RAG with structured, curated knowledge.

Render hierarchical system diagrams as PNGs from YAML definitions using a four-level ontology of networks, factories, machines, and nodes.