MCP Tool Server is a project that demonstrates how to implement and use Anthropic's Model Context Protocol (MCP) with AWS Bedrock. It provides a client implementation capable of interacting with MCP-enabled tools via AWS Bedrock’s runtime service, supporting both stdio and sse communication modes.
The server enables seamless integration with AWS Bedrock, allowing developers to utilize advanced tooling capabilities in their AI models. It simplifies the interaction between tools and models by handling format conversion, asynchronous communication, and structured logging for debugging purposes.
Developers and organizations working with AWS Bedrock and Anthropic's MCP can benefit from this tool. It is especially useful for those who need clear examples of implementing and using MCP-enabled tools with Amazon Nova models or other compatible systems.
The MCP Tool Server is designed to run within environments where AWS Bedrock access is available. It requires Python 3.10 or higher, an AWS account, configured credentials, and the UV package manager. The source code is hosted on GitHub under davidshtian/MCP-on-AWS-Bedrock.
You should consider using MCP Tool Server when building applications that require model-tool interactions through AWS Bedrock. It's particularly helpful during development phases that involve testing, debugging, and integrating multiple tools into AI workflows.
Yes, prerequisites include having Python 3.10 or higher, an AWS account with Bedrock access, properly configured AWS credentials, and the UV package manager installed.
To run the stdio client, execute 'uv pip install boto3' followed by 'uv run client_stdio.py'. This will initialize the connection to AWS Bedrock, start the MCP tool server, list available tools, and handle communications.
Key features include seamless integration with AWS Bedrock runtime, tool format conversion for compatibility, asynchronous communication handling, and structured logging for debugging.
Yes, contributions are welcome! You can submit issues and pull requests to improve the implementation. The project is licensed under the MIT License.
Yes, you can refer to the official documentation on Anthropic MCP, MCP Python SDK, and AWS Bedrock for more information.
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.