The cooper-hewitt-mcp is a Model Context Protocol (MCP) server designed to interact with the Cooper Hewitt Museum's collection API. It allows users to programmatically search and retrieve detailed information about museum objects.
The cooper-hewitt-mcp was created to facilitate programmatic interaction with the Cooper Hewitt Museum's collection API, providing tools to search for objects and retrieve detailed object information efficiently.
The cooper-hewitt-mcp was developed by behole (Frank Fiegel), as part of the 'punkpeye' project, with acknowledgments to Cooper Hewitt, Smithsonian Design Museum and the Model Context Protocol SDK.
The cooper-hewitt-mcp repository is hosted on GitHub and can be accessed via the URL: https://github.com/behole/cooper-hewitt-mcp.
The initial release of cooper-hewitt-mcp (v0.0.1) occurred on January 17, 2025.
To run cooper-hewitt-mcp, you need Node.js (version 16+ recommended) and npm (Node Package Manager).
You can install cooper-hewitt-mcp by cloning the repository using 'git clone https://github.com/behole/cooper-hewitt-mcp.git', navigating into the directory, and running 'npm install' to install dependencies.
Create a .env file in the project root, obtain an API token from the Cooper Hewitt API, and add it to the .env file in the format: COOPER_HEWITT_API_TOKEN=your_api_token_here.
Two primary tools are available: 'search-objects' for searching objects in the Cooper Hewitt collection, and 'get-object' for retrieving detailed information about a specific museum object.
You can start the server by running 'node index.js' in the project directory.
To contribute, fork the repository, create a feature branch, commit your changes, push to the branch, and open a Pull Request.
The exact license is not specified in the provided content but should be defined in the LICENSE file within the repository (e.g., MIT or Apache 2.0).
MCP (Model Context Protocol) is an open protocol designed to standardize how applications provide context information to large language models (LLMs). Like a 'USB-C port' for AI applications, MCP ensures AI models can seamlessly connect with various data sources and tools.
An MCP Server is a server that supports the MCP protocol, enabling the exchange of contextual information between applications and AI models in a standardized way. It provides developers with an easy way to integrate AI models with databases, APIs, or other data sources.
An MCP Server eliminates the complexity of developing custom adapters by unifying the connection between AI models and various data sources. Whether you're a developer, data scientist, or AI app builder, an MCP Server simplifies the integration process, saving time and resources.
An MCP Server acts as an intermediary bridge, converting contextual information from various data sources into a format that AI models can understand. By adhering to the MCP protocol, it ensures data is transmitted between applications and AI models in a standardized manner.
At mcpserver.shop, you can browse our MCP Server Directory. The directory is categorized by industry (e.g., finance, healthcare, education), and each server comes with detailed descriptions and tags to help you quickly find the option that suits your needs.
The MCP Server Directory on mcpserver.shop is free to browse. However, some servers are hosted by third-party providers and may involve usage fees. Check the detailed page of each server for specific information.
MCP Servers support a wide range of data sources, including databases, APIs, cloud services, and custom tools. The flexibility of the MCP protocol allows it to connect almost any type of data source to AI models.
MCP Servers are primarily designed for developers, data scientists, and AI app builders. However, mcpserver.shop provides detailed documentation and guides to help users of varying technical levels get started easily.
Yes, MCP is an open-source protocol that encourages community participation and collaboration. For more details or to contribute, visit the official MCP documentation.
On mcpserver.shop, each MCP Server’s detailed page includes the provider’s contact information or a link. You can directly reach out to the provider for more details or technical support.