Academic figure generation MCP server for AI agents — turn papers into publication-ready medical and scientific figures
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An architecture-planning agent for Academic Figures MCP that uses Domain-Driven Design (DDD), a way to organize software around its business concepts, and a project memory bank.
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A project assistant that reads a project's Memory Bank—a collection of files recording its context, patterns, decisions, and progress—to answer questions in Traditional Chinese.
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Asset-Aware MCP document workflow agent for citation-ready PDF/DOCX/DFM/table/figure work.
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A code-audit agent that reviews software across architecture, security, code quality, testing, and documentation. It produces a structured report with severity levels and repair suggestions.
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A coding agent configured to implement, debug, refactor, and test software using Domain-Driven Design, an approach that organizes code around the real concepts and rules of a business domain.
Agent
An agent prompt for reading a project's memory files, source code, and documentation, then producing a structured summary. The example project is an MCP server for turning PubMed research into academic figures.
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A debugging agent that investigates software problems using error details, project structure, and the project's stored history of decisions.
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An AI assistant for carefully analyzing difficult engineering problems before recommending a solution. It covers algorithms, software architecture, technology choices, performance issues, and root-cause analysis.
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A coordinator for complex software tasks that breaks work into smaller assignments and delegates them to specialized AI workers. It then tracks the work and combines the results.
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A research assistant for finding biomedical papers in PubMed and managing references in Zotero. PubMed is a database of biomedical literature, and Zotero is a tool for organizing citations.
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A read-only codebase research agent that scans a project, traces how its parts connect, and writes an investigation report. Read-only means it does not change files.
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A code-review workflow in which Claude, GPT, and Gemini review the same project from different angles, then a chairperson combines their findings into one report.
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A Claude-based code-review agent that examines security, type correctness, edge cases, and error handling. Type checking verifies that values are used consistently, while edge cases are unusual or boundary inputs.
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A Gemini-based code reviewer focused on software structure, tests, documentation, and CI/CD, the automated build and test process.
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A GPT-based code reviewer that checks performance, readability, design patterns, maintainability, and separation between software layers. It returns the review in Traditional Chinese, while keeping technical terms in English.
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An automated test-running agent for Python projects that uses pytest, a Python testing tool, to run tests, inspect failures, and try small local fixes.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: