"EarningsPrism MCP (Model Context Protocol) Configuration" matching MCP servers:

Turn natural language into 3D models in Fusion 360. 64 CAD tools including sketches, extrudes, fillets,and JIS standard parts.

Static codebase analysis as MCP tools — give AI coding agents a map of your repo instead of letting them burn half their tokens rediscovering it file by file.

A Model Context Protocol server for deep codebase understanding of Python projects, focusing on data analysis and scientific computing. It provides architectural analysis, pattern detection, dependency mapping, test coverage analysis, and AI-optimized context generation.

Enables AI agents to query Backstage catalog data as a typed graph over MCP, answering blast-radius, ownership and escalation, dependency, path, change-risk, and catalog-drift questions through bounded read-only tools.

An MCP server for managing Domain-Driven Design models using Context Mapper's CML, with tools to create, update, and visualize bounded contexts, aggregates, and relationships.

Local-first MCP server that gives AI assistants codebase intelligence—code graph, drift analysis, vulnerability attribution, and version-correct library docs—all from the user's machine.

MCP server for rendering Object-Process Methodology (OPM) models from YAML to SVG diagrams and OPL sentences, with validation and generation capabilities.

Validates and renders declarative JSON diagram specs to themeable SVG. The format has no coordinates, so a model writes structure and the renderer does the layout; tools: validate, render, kinds.

15 AI-powered UML diagram tools for coding agents. Generates class, sequence, state, ER, threat model, deployment and architecture diagrams in Mermaid syntax. Works in Claude Code, Cursor and Windsurf.

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

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.

Enables coding agents to write repository documents (READMEs, RFCs, design docs, ADRs) from verified codebase facts, using a separate model for drafting and agent fact-checking for accuracy.

Enables auto-configuration and validation of React components against a glassmorphic design token system using an AST correction engine. It supports managing UI presets, enforcing design uniformity in Monaco IDE, and exporting tokens as CSS, Tailwind, or JavaScript variables.

Model Context Protocol (MCP) server for @imqueue — lets AI coding agents (Claude Code, Cursor and others) search the docs, scaffold typed services & clients and use @imqueue/cli live.

Generates UML and other diagrams (30+ types) via the Model Context Protocol, supporting multiple output formats and deployment options.

Connects Claude directly to Godot 4 projects to read and manipulate scenes, nodes, scripts, and assets within the editor. It enables real-time scene tree management, script editing, and resource configuration through a local Node.js bridge and GDScript plugin.

Enables AI coding agents to discover, convert, and synchronize Draw.io C4 and UML diagrams into Mermaid Markdown, providing architectural context and guardrails during chat sessions.

Provides enterprise architecture knowledge tools that ground agents in curated patterns, enabling translation of messy enterprise asks into realistic architecture recommendations, platform selection, risk checks, and brand context retrieval.

Enables AI hosts to generate editable online diagrams (flowcharts, mindmaps, UML, and more) from natural language or Mermaid, using a ProcessOn account via the Model Context Protocol.

Enables AI assistants to generate and validate 30+ UML and other diagram types (Mermaid, D2, Graphviz, BPMN, C4, and more) through the Model Context Protocol, returning rendered SVG, PNG, PDF, JPEG, or base64 output via Kroki, PlantUML, and Mermaid backends.

Enables AI assistants to directly control Autodesk 3ds Max through natural language to create models, set materials, adjust lighting, and automate animations. It bridges the Model Context Protocol with 3ds Max via a TCP socket to execute Python and MAXScript commands.

@codapult/guard is local-first, model-agnostic architecture guardrail software for AI coding agents. Use it to detect architectural drift, enforce approved software architecture rules, and check code changes in JavaScript and TypeScript projects.

Enables analysis of any GitHub repository to get architecture, file roles, execution flows, system design Q\&A, and structured agent context. Works with MCP-compatible clients like Claude Desktop, Cursor, and Windsurf.

An MCP server designed for React Native and Expo development that provides specialized tools for project scaffolding, architectural best practices, and troubleshooting. It enables AI assistants to guide users through setup, navigation configuration, and CI/CD processes using modern stacks like NativeWind and Zustand.

A cross-project knowledge graph for MCP that maps features across mobile, backend, and admin codebases, giving AI agents full-stack context.

Provides Model Context Protocol access to the SEAF ArchTool REST API, enabling agents to inspect sections and entities, navigate relations, query datasets, and run JSONata expressions against a SEAF portal.

Model Context Protocol server that lets AI agents drive StarUML programmatically — generate UML diagrams, execute commands, and manage elements and projects via HTTP.

Serves graph-native code questions from a TypeScript codebase as an MCP server. It extracts structural graphs via tree-sitter and HydraDB to answer callers, impact, and context queries.

A Model Context Protocol server that manages structured technical spike investigations and generates Architecture Decision Records through an enforced four-phase workflow. It enables developers to track exploration branches, document adversarial challenges, and maintain persistent state across multiple sessions.

This MCP server enables AI models to analyze local Python codebases using abstract syntax trees, providing tools for file structure analysis, symbol search, import graphing, docstring auditing, and refactoring prompts without loading entire source files into context.