Model Context Protocol (sse) servers
Model Context Protocol Servers with SSE
What is Model Context Protocol (sse) servers?
Model Context Protocol (sse) servers are reference implementations for the Model Context Protocol (MCP) that utilize Server-Sent Events (SSE) to provide secure and controlled access to AI tools and data sources.
How to use Model Context Protocol (sse) servers?
To use these servers, developers can implement them using either the Typescript MCP SDK or the Python MCP SDK, allowing for integration into various applications that require AI capabilities.
Key features of Model Context Protocol (sse) servers?
- Secure and controlled access to AI tools and data sources.
- Implementation options using Typescript or Python SDKs.
- Support for JSON-RPC batching to improve efficiency.
- Enhanced authorization framework based on OAuth 2.1.
- Support for multiple data types including text, image, and audio.
Use cases of Model Context Protocol (sse) servers?
- Enabling enterprises to connect employees to AI tools in a controlled manner.
- Facilitating secure access to AI-driven applications in various industries.
- Supporting multimedia applications with audio data handling.
FAQ from Model Context Protocol (sse) servers?
- What is the purpose of the MCP servers?
They provide a framework for enterprises to manage AI tool access securely and efficiently.
- Are the community servers reliable?
Community servers are untested and should be used at your own risk, as they are not officially endorsed.
Model Context Protocol (sse) servers
This repository is a collection of reference implementations for the Model Context Protocol (MCP) with SSE, as well as references to community built servers and additional resources.
For many enterpises, it's no way to have each employees to connect to AI Tools without control and governance, it's critical to have these MCP tools with remote connect capabilities (sse) and allow enterprise to create a reliable and responsible environemnt to run AI realted usecases.
All the MCP servers listed in this repository showcase the versatility and extensibility of MCP, demonstrating how it can be used to give Large Language Models (LLMs) secure, controlled access to tools and data sources.
Each MCP server is implemented with either the Typescript MCP SDK or Python MCP SDK.
Note: Lists in this README are maintained in alphabetical order to minimize merge conflicts when adding new items.
MCP Spec
There are two mcp spec released at 2025 Mar/30, let's quick compare the differnece of these two specs:
To organize the differences clearly, the following table encapsulates the comparison:
| Feature/Aspect | Description | 2024-11-05 (Final) | 2025-03-26 (Latest) |
|---|---|---|---|
| Authorization Framework | A system to manage and control access to MCP servers, ensuring that only authorized users or applications can interact with them. | No specific framework mentioned; general guidelines for user consent. | Added a comprehensive framework based on Oatuh 2.1 for standardized authorization processes. |
| Transport Layer | The method used for data transmission between clients and servers. | HTTP with Server-Sent Events (HTTP+SSE) | Replaced with Streamable HTTP, which likely offers more flexibility or improved performance. |
| JSON-RPC Batching | The ability to send multiple JSON-RPC requests in a single message, which can improve efficiency by reducing network overhead. | Not supported | Supported, allowing for batch processing of requests. |
| Tool Annotations | Descriptive labels or metadata for tools that indicate their behavior, such as whether they are read-only or can perform destructive operations. | Not mentioned | Added to provide better understanding and control over tool usage. |
| ProgressNotification | Notifications that inform about the progress of ongoing operations. | Did not have a message field | Added a message field to provide descriptive status updates, enhancing user experience and debugging. |
| Data Support | The types of data that the protocol can handle and transmit. | Text and Image | Added support for Audio data, expanding the range of content types that can be managed. |
| Completions Capability | A feature that allows for providing suggestions or completions for arguments in requests, which can be useful for user interfaces or to assist in constructing requests. | Not explicitly mentioned | Added to support argument autocompletion, likely improving usability and efficiency. |
Implications and Observations
The updates from 2024-11-05 to 2025-03-26 indicate a focus on enhancing security, flexibility, and usability.
The addition of an OAuth 2.1-based authorization framework and Streamable HTTP transport suggests a move toward more robust and scalable implementations.
The inclusion of audio data support and tool annotations could significantly expand MCP’s applicability, particularly in multimedia and complex AI workflows.
The unexpected detail of audio support, not previously highlighted, may indicate a shift toward more versatile AI interactions, potentially impacting industries like voice assistants or multimedia content analysis.
🌟 Reference Servers
These servers aim to demonstrate MCP features and the TypeScript and Python SDKs.
- Weather - Provides weather forecasts and alert for U.S states
🤝 Third-Party Servers
🌎 Community Servers
A growing set of community-developed and maintained servers demonstrates various applications of MCP across different domains.
Note: Community servers are untested and should be used at your own risk. They are not affiliated with or endorsed by Anthropic.
