Skillget

modular-patchbay

mcp
Security Audit
Fail
Health Warn
  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 5 GitHub stars
Code Fail
  • execSync — Synchronous shell command execution in bin/modular-studio.ts
  • process.env — Environment variable access in playwright.config.ts
Permissions Pass
  • Permissions — No dangerous permissions requested
Purpose
This tool is a visual IDE and MCP server designed for building and configuring AI agent systems. It allows developers to visually design knowledge pipelines, connect data sources, and export agent configurations for multiple platforms.

Security Assessment
Overall risk is rated as Medium. The primary security concern is the confirmed use of synchronous shell command execution (`execSync`) within the codebase. While executing shell commands is a common requirement for development servers, it creates a potential attack vector if malicious user input reaches this function unchecked. The tool does not request inherently dangerous permissions and no hardcoded secrets were detected. It does access environment variables, which is expected for managing LLM provider configurations, but users should ensure their `.env` files are properly secured and never committed.

Quality Assessment
The project is actively maintained, with its most recent code push happening today. It uses the standard, permissive MIT license, which is great for open-source adoption. However, community trust and visibility are currently very low. With only 5 GitHub stars, the tool has not yet been widely tested or vetted by the broader developer community. This means bugs or security vulnerabilities are more likely to be undiscovered compared to heavily established tools.

Verdict
Use with caution — the codebase requires local execution privileges that demand a manual code review before deploying in sensitive environments.
SUMMARY

Context engineering IDE for AI agents. Design knowledge pipelines, not just prompts.

README.md

Modular Studio

The context engineering IDE for AI agents.

Build AI agents that truly understand your codebase, documentation, and tools — through intelligent knowledge pipelines, not just prompts.

Quick Start

npx modular-studio

Opens at localhost:4800.

What It Does

Modular Studio is a visual IDE for designing AI agent systems. You describe what you want → it generates a complete agent configuration with persona, constraints, objectives, workflow, and tool selection — all grounded in your actual knowledge sources.

The Workflow

  1. Describe — Write what your agent should do (or pick a template)
  2. Generate — AI creates a full agent config from your description via meta-prompt
  3. Knowledge — Connect repos, files, connectors. See what's missing.
  4. Tools — Pick MCP servers and skills from 150+ integrations
  5. Memory — Configure conversation memory strategy
  6. Review — Inspect and refine: persona, constraints, objectives, workflow
  7. Test — Chat with your agent, see the full pipeline trace
  8. Qualify — Run structured evaluations against test cases
  9. Export — Output for Claude Code, OpenClaw, Codex, Amp, or generic JSON

What Makes It Different

Prompt Engineering RAG Tools Modular Studio
Starting point Manual writing Upload docs Describe in natural language
Knowledge Copy-paste Chunk embeddings Tree-aware semantic retrieval
Visibility None Similarity scores Full pipeline observability
Output One prompt API endpoint Multi-target agent definitions
Iteration Rewrite Re-embed Visual refinement + qualification

Key Features

  • 🧠 Meta-Prompt Generation — Describe your agent, get a complete configuration
  • 🌳 Tree-Aware Retrieval — Knowledge pipeline understands document and code structure
  • 📊 Pipeline Observability — See exactly how context flows: source assembly → retrieval → provenance
  • 🔌 150+ MCP Connectors — GitHub, Notion, Slack, HubSpot, and more
  • 🏗️ Agent Library — Save, version, and manage multiple agents
  • 📋 Structured Review — Identity, persona, constraints, objectives, workflow — all editable
  • 🧪 Built-in Testing — Chat with your agent, run teams, trace every step
  • 📤 Multi-Target Export — Claude Code (.md), OpenClaw (.yaml), Codex (.json), Amp, generic

Installation

From npm

# Run directly
npx modular-studio

# Or install globally
npm install -g modular-studio
modular-studio --open

From Source

git clone https://github.com/VictorGjn/modular-patchbay.git
cd modular-patchbay
npm install --legacy-peer-deps
npm run dev

Frontend: http://localhost:5173 · Backend: http://localhost:4800

Configuration

Providers

Connect at least one LLM provider in Settings → Providers:

  • Claude Agent SDK — Zero-config if running inside Claude Code
  • Anthropic — API key required
  • OpenAI — API key required
  • OpenRouter — API key for aggregated model access
  • Google — API key for Gemini models

Knowledge Sources

  • Local Files — Drag and drop markdown, code, or documents
  • Git Repos — Clone and index any GitHub repository
  • Connectors — Notion, Slack, HubSpot via MCP

Requirements

  • Node.js 18+
  • LLM API Key (Anthropic, OpenAI, or compatible provider)

Architecture

src/
├── tabs/           # Wizard tab components (Describe, Knowledge, Tools, etc.)
├── panels/         # Sub-panels (AgentBuilder, review sections, pipeline)
├── components/     # Shared components (AgentLibrary, Topbar, InlineTraceView)
├── services/       # Pipeline services (treeIndexer, compress, contextAssembler)
├── store/          # Zustand stores (console, trace, conversation, memory)
├── utils/          # Agent generation, export, analysis utilities
└── layouts/        # WizardLayout, DashboardLayout
server/
├── routes/         # API routes (agents, providers, conversations)
└── services/       # Backend services (agentStore, embeddings)

License

Apache 2.0 — Free for commercial and open source use.

Links

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