"Files formatted in JSON" matching MCP servers:

Embeds live, interactive Tableau dashboards in ChatGPT, pushing mark selections to the model so questions about specific data points are answered with live queried numbers.

Renders word-sized charts — sparklines, bars, bullets and 100+ more types — to self-contained SVG with generated alt text, small enough to sit inline in a model's reply or a table cell. Three tools: find the right chart for a question, get its wiring, and render it.

MCP server that lets agents create, display, and export rich UI widgets (cards, dashboards, charts, forms) inline in conversations, with interactive iframe support in MCP Apps hosts and PNG image fallback for other clients.

MCP server for creating interactive Vega-Lite data visualizations that render inline in chat via MCP Apps.

An MCP server that generates diagrams from Mermaid code in multiple formats (PNG, PDF, SVG).

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.

MCP server that provides a live, terminal-native layered dependency map for AI coding assistants, with tools to track and visualize development progress in real time.

Enables querying SQLite databases in plain language through MCP, letting clients like Claude Code inspect schemas and run read-only SQL.

An MCP server that lets Claude or ChatGPT read, create, and edit mind maps stored in a GitHub repository, with support for local and HTTP transport.

Intelligence layer for AI that enables querying across revenue, errors, identity, and analytics layers in plain English, returning rendered charts and dashboards.

Wraps a climate data-processing pipeline so agents can inspect the config schema and available sample CSVs, validate an inline JSON config, and run the pipeline to return a monthly summary table plus a rendered plot, with file access sandboxed to the data and outputs directories.

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.

Turns a CSV — or a public dataset named in plain English — into an animated chart video. Every numeric claim in the generated narration is recomputed from the source rows before export, and a claim that does not reconcile blocks the export rather than shipping.

Universal MCP server for generating word clouds using ShapeWords, enabling creation of SVG, JSON, or PNG word clouds from text with extensive customization options.

Enables AI agents to render interactive user interfaces such as forms, dashboards, charts, tables, and wizards directly in MCP-compatible clients. Supports structured data collection and richer interactions beyond text responses.

Lets agents construct Mermaid diagrams from structured JSON IR and render them as PNG or SVG.

Enables assistants to read and analyze construction schedules like a scheduler: CPM, float, critical paths, DCMA 14-point, logic checks, update-to-update comparison, baseline variance, and S-curves from P6 XER and MS Project files.

Enables LLMs to author, validate, and render Blueprint Chart (.bpc) files with structured dataviz pedagogy and a tight parse + render feedback loop.

Turns an LLM into a Maltego CE investigation copilot, enabling AI-assisted OSINT investigations by building, analyzing, and exporting Maltego graph files.

Visualizes conversations as structured hierarchical mind maps by injecting a prompt that instructs the LLM to generate a JSON mind map — no external APIs required.