What is MCP and how does this server use it?
MCP (Model Context Protocol) is a standard for connecting LLMs to external tools and data sources. This server implements an MCP endpoint so that Claude Desktop can call the Science Museum Group API.
@opensourcedev90s
Basic information
MCP Server for the UK Science Museum Group
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"uk-science-museum-group-mcp": {
"command": "uv",
"args": [
"venv"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A Python MCP (Model Context Protocol) server that enables large language models, such as Claude, to fetch data from the UK Science Museum Group’s Collections Online API. It is designed for Claude Desktop on macOS and Windows.
Install UV (a Python package manager) on macOS or Windows, then edit your Claude Desktop configuration file (claude_desktop_config.json) to add the server entry shown in the README. After restarting Claude Desktop, you can query the museum’s collections directly through Claude.
MCP (Model Context Protocol) is a standard for connecting LLMs to external tools and data sources. This server implements an MCP endpoint so that Claude Desktop can call the Science Museum Group API.
You need Python and UV installed. The server is distributed as a Python package (`science-museum-mcp`) and is executed via `uvx`. No additional API key or authentication is required for the public collection API.
All data is retrieved in real‑time from the UK Science Museum Group’s official Collections Online API (documented at their GitHub wiki). The server does not store or cache any data locally.
The READTE only demonstrates configuration for Claude Desktop. The server follows the MCP standard, so in principle it may work with other hosts, but no other integrations are documented.
Install UV, then add the following to your `claude_desktop_config.json`: `{ "mcpServers": { "scienceMuseum": { "command": "uvx", "args": ["science-museum-mcp"] } } }`. Detailed paths for macOS and Windows are provided in the README.
OrangePro local-first CLI + MCP server for behavior mapping, grounded test generation, and dynamic proof.

Agent Trust — open profile + reference implementation for proving what an autonomous AI agent is authorized to do: identity, delegation with attenuation, proof-of-possession, attestations, tamper-evident provenance. Buil

Turn Perfex CRM into an AI-ready workspace. This MCP server exposes your full REST API to Claude, ChatGPT and any AI agent, so leads, invoices and tasks are one prompt away.

Most MCP servers hand your agent documentation. This one hands it a renderer. Write a single React Native codebase that ships native AR to phones and VR to headsets, then let your agent validate every prop, check each pl
Query your team's drift, vulnerability, and migration data from any AI assistant. Vibgrate MCP connects Cursor, Claude, ChatGPT, Windsurf, or VS Code to Vibgrate Cloud: 51 tools for DriftScores, CVEs and EOL runtimes, up
Comments