Toolbox▌
by ai-zerolab
Toolbox integrates APIs and services for LLM command execution, UI/UX design, and risk management API integration platfo
Integrates with external APIs and services to provide command execution, Figma file interaction, and file operations, enhancing LLM capabilities for UI/UX design, file management, and service interactions.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / UI/UX designers working with Figma
- / Developers needing system command execution
- / File management automation
- / Design-to-code workflows
capabilities
- / Execute command line instructions
- / Access Figma files and components
- / Perform file operations
- / Integrate with external APIs
- / Query Figma styles and design tokens
what it does
Provides command-line execution, Figma file access, and file operations through MCP protocol. Extends LLM capabilities to interact with external services and APIs.
about
Toolbox is a community-built MCP server published by ai-zerolab that provides AI assistants with tools and capabilities via the Model Context Protocol. Toolbox integrates APIs and services for LLM command execution, UI/UX design, and risk management API integration platfo It is categorized under developer tools.
how to install
You can install Toolbox in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
Apache-2.0
Toolbox is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
mcp-toolbox
A comprehensive toolkit for enhancing LLM capabilities through the Model Context Protocol (MCP). This package provides a collection of tools that allow LLMs to interact with external services and APIs, extending their functionality beyond text generation.
- GitHub repository: https://github.com/ai-zerolab/mcp-toolbox/
- (WIP)Documentation: https://ai-zerolab.github.io/mcp-toolbox/
Features
*nix is our main target, but Windows should work too.
- Command Line Execution: Execute any command line instruction through LLM
- Figma Integration: Access Figma files, components, styles, and more
- Extensible Architecture: Easily add new API integrations
- MCP Protocol Support: Compatible with Claude Desktop and other MCP-enabled LLMs
- Comprehensive Testing: Well-tested codebase with high test coverage
Installation
Using uv (Recommended)
We recommend using uv to manage your environment.
# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh # For macOS/Linux
# or
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" # For Windows
Then you can use uvx "mcp-toolbox@latest" stdio as commands for running the MCP server for latest version. Audio and memory tools are not included in the default installation., you can include them by installing the all extra:
[audio] for audio tools, [memory] for memory tools, [all] for all tools
uvx "mcp-toolbox[all]@latest" stdio
Installing via Smithery
To install Toolbox for LLM Enhancement for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @ai-zerolab/mcp-toolbox --client claude
Using pip
pip install "mcp-toolbox[all]"
And you can use mcp-toolbox stdio as commands for running the MCP server.
Configuration
Environment Variables
The following environment variables can be configured:
FIGMA_API_KEY: API key for Figma integrationTAVILY_API_KEY: API key for Tavily integrationDUCKDUCKGO_API_KEY: API key for DuckDuckGo integrationBFL_API_KEY: API key for Flux image generation API
Memory Storage
Memory tools store data in the following locations:
- macOS:
~/Documents/zerolab/mcp-toolbox/memory(syncs across devices via iCloud) - Other platforms:
~/.zerolab/mcp-toolbox/memory
Full Configuration
To use mcp-toolbox with Claude Desktop/Cline/Cursor/..., add the following to your configuration file:
{
"mcpServers": {
"zerolab-toolbox": {
"command": "uvx",
"args": ["--prerelease=allow", "mcp-toolbox@latest", "stdio"],
"env": {
"FIGMA_API_KEY": "your-figma-api-key",
"TAVILY_API_KEY": "your-tavily-api-key",
"DUCKDUCKGO_API_KEY": "your-duckduckgo-api-key",
"BFL_API_KEY": "your-bfl-api-key"
}
}
}
}
For full features:
{
"mcpServers": {
"zerolab-toolbox": {
"command": "uvx",
"args": [
"--prerelease=allow",
"--python=3.12",
"mcp-toolbox[all]@latest",
"stdio"
],
"env": {
"FIGMA_API_KEY": "your-figma-api-key",
"TAVILY_API_KEY": "your-tavily-api-key",
"DUCKDUCKGO_API_KEY": "your-duckduckgo-api-key",
"BFL_API_KEY": "your-bfl-api-key"
}
}
}
}
You can generate a debug configuration template using:
uv run generate_config_template.py
Available Tools
Command Line Tools
| Tool | Description |
|---|---|
execute_command | Execute a command line instruction |
File Operations Tools
| Tool | Description |
|---|---|
read_file_content | Read content from a file |
write_file_content | Write content to a file |
replace_in_file | Replace content in a file using regular expressions |
list_directory | List directory contents with detailed information |
Figma Tools
| Tool | Description |
|---|---|
figma_get_file | Get a Figma file by key |
figma_get_file_nodes | Get specific nodes from a Figma file |
figma_get_image | Get images for nodes in a Figma file |
figma_get_image_fills | Get URLs for images used in a Figma file |
figma_get_comments | Get comments on a Figma file |
figma_post_comment | Post a comment on a Figma file |
figma_delete_comment | Delete a comment from a Figma file |
figma_get_team_projects | Get projects for a team |
figma_get_project_files | Get files for a project |
figma_get_team_components | Get components for a team |
figma_get_file_components | Get components from a file |
figma_get_component | Get a component by key |
figma_get_team_component_sets | Get component sets for a team |
figma_get_team_styles | Get styles for a team |
figma_get_file_styles | Get styles from a file |
figma_get_style | Get a style by key |
XiaoyuZhouFM Tools
| Tool | Description |
|---|---|
xiaoyuzhoufm_download | Download a podcast episode from XiaoyuZhouFM with optional automatic m4a to mp3 conversion |
Audio Tools
| Tool | Description |
|---|---|
get_audio_length | Get the length of an audio file in seconds |
get_audio_text | Get transcribed text from a specific time range in an audio file |
Memory Tools
| Tool | Description |
|---|---|
think | Use the tool to think about something and append the thought to the log |
get_session_id | Get the current session ID |
remember | Store a memory (brief and detail) in the memory database |
recall | Query memories from the database with semantic search |
forget | Clear all memories in the memory database |
Markitdown Tools
| Tool | Description |
|---|---|
convert_file_to_markdown | Convert any file to Markdown using MarkItDown |
convert_url_to_markdown | Convert a URL to Markdown using MarkItDown |
Web Tools
| Tool | Description |
|---|---|
get_html | Get HTML content from a URL |
save_html | Save HTML from a URL to a file |
search_with_tavily | Search the web using Tavily (requires API key) |
search_with_duckduckgo | Search the web using DuckDuckGo (requires API key) |
Flux Image Generation Tools
| Tool | Description |
|---|---|
flux_generate_image | Generate an image using the Flux API and save it to a file |
Usage Examples
Running the MCP Server
# Run with stdio transport (default)
mcp-toolbox stdio
# Run with SSE transport
mcp-toolbox sse --host localhost --port 9871
Using with Claude Desktop
- Configure Claude Desktop as shown in the Configuration section
- Start Claude Desktop
- Ask Claude to interact with Figma files:
- "Can you get information about this Figma file: 12345abcde?"
- "Show me the components in this Figma file: 12345abcde"
- "Get the comments from this Figma file: 12345abcde"
- Ask Claude to execute command line instructions:
- "What files are in the current directory?"
- "What's the current system time?"
- "Show me the contents of a specific file."
- Ask Claude to download podcasts from XiaoyuZhouFM:
- "Download this podcast episode: https://www.xiaoyuzhoufm.com/episode/67c3d80fb0167b8db9e3ec0f"
- "Download and convert to MP3 this
FAQ
- What is the Toolbox MCP server?
- Toolbox is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Toolbox?
- This profile displays 31 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.4 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
List & Promote Your MCP Server
Share your MCP server with the developer community
Ratings
4.4★★★★★31 reviews- ★★★★★Hassan Robinson· Dec 16, 2024
According to our notes, Toolbox benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Zaid Li· Dec 12, 2024
Toolbox reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Chaitanya Patil· Dec 8, 2024
According to our notes, Toolbox benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Mateo Ramirez· Dec 4, 2024
Toolbox has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Piyush G· Nov 27, 2024
We wired Toolbox into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Mateo Abbas· Nov 23, 2024
Toolbox is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Zaid Kim· Nov 19, 2024
Strong directory entry: Toolbox surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Ava Okafor· Nov 7, 2024
We wired Toolbox into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Camila Kim· Oct 26, 2024
Toolbox is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Shikha Mishra· Oct 18, 2024
Toolbox is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
showing 1-10 of 31