"DeepSeek JSONL阅读能力" matching MCP servers:

Analyzes C++ source code to automatically generate UML class diagrams in PlantUML format, extracting classes, inheritance relationships, and member visibility from directories or file contents.

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.

Provides UI architecture analysis for converting Figma designs or web pages into reusable UI code blocks with effort estimation in CSV format.

MCP server that enables AI assistants to create, parse, render, and validate Draw.io diagrams programmatically.

An Excalidraw editor for DeepSeek Harness that lets AI models create, edit, and inspect diagrams, including image capture and revision management.

Enables AI agents to record and retrieve architectural decision records, check precedent before making decisions, and avoid repeating past mistakes or contradicting settled choices.

Architecture-index MCP tools for kernelee apps that combine static analysis and runtime wiring into a JSON index, enabling coding agents to query control flow and dependencies via the Model Context Protocol.

MCP server that analyzes codebases to provide dependency graphs, impact analysis, and file insights across 15+ programming languages, enabling AI assistants to understand project structure and navigate code efficiently.

Cross-stack MCP server that scans frontend and backend code together, detects mismatches like phantom calls, dead endpoints, and field drift, and provides a full-stack health audit.

Provides a semantic understanding of your codebase by parsing with tree-sitter and building a graph of symbols and dependencies. Enables AI assistants to navigate code, analyze changes, and discover architecture using 18 tools with minimal context overhead.

Enforces a rigorous spec-driven engineering workflow for AI coding assistants, requiring requirements, design, and task planning before any code is written.