pulsemcp Safe content atomic mcp-remote

Toolbox

This MCP server implementation provides a comprehensive toolbox for enhancing Large Language Models (LLMs) through various API integrations and utilities. Developed by ai-zerolab, it offers tools for executing command line instructions, interacting with Figma files, and performing file operations. The server is designed with an extensible architecture, allowing easy addition of new API integrations. It supports Claude Desktop and other MCP-enabled LLMs, making it suitable for a wide range of use cases including UI/UX design workflows, automated file management, and enhanced LLM interactions with external services.

Cognium trust score

50%

Tier

Unverified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.

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Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: ai-ml
Source: PulseMCP
Repository: github.com/ai-zerolab/mcp-toolbox
Author type: human
Updated: 2026-08-29

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MCP

Resolve Toolbox from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"