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MCP SSE Server (mcp-ectors): Scalable Real-Time AI Infrastructure - MCP Implementation

MCP SSE Server (mcp-ectors): Scalable Real-Time AI Infrastructure

MCP SSE Server (mcp-ectors): Enterprise-grade AI infrastructure powered by actor-based computing, delivering seamless scalability and real-time performance for mission-critical workloads.

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About MCP SSE Server (mcp-ectors)

What is MCP SSE Server (mcp-ectors): Scalable Real-Time AI Infrastructure?

Designed as the enterprise-grade backbone for agentic AI workflows, MCP SSE Server (mcp-ectors) bridges large language models (LLMs) with external tools, resources, and prompts. Built with Rust and actor-based architecture, it enables high-concurrency interactions while maintaining strict performance standards. This infrastructure acts as a universal interface—like a USB protocol for AI—allowing LLMs to dynamically access capabilities through registered routers.

How to use MCP SSE Server (mcp-ectors): Scalable Real-Time AI Infrastructure?

1. Installation: Install Rust and Cargo, then clone the repository via `git clone`.
2. Server Setup: Run `cargo run` to start the server on http://localhost:8080/sse.
3. Integration: Use Goose Desktop to connect via SSE transport and execute pre-built examples like counter operations or "Hello World" greetings.
4. Customization: Extend functionality by implementing the Router trait for new use cases, then register them via Router Service Manager.

MCP SSE Server (mcp-ectors) Features

Key Features of MCP SSE Server (mcp-ectors): Scalable Real-Time AI Infrastructure?

  • Performance-Optimized Architecture: Rust’s memory safety combined with actor concurrency ensures low-latency, high-throughput operations.
  • Connection Reuse: Deploy multiple routers on a single connection, reducing overhead and simplifying resource management.
  • Router Ecosystem: Dynamically register tools, prompts, and resources as modular routers through standardized interfaces.
  • Transport Flexibility: Current SSE support with planned stdio and WASI extensions for diverse deployment scenarios.

Use cases of MCP SSE Server (mcp-ectors): Scalable Real-Time AI Infrastructure?

1. Enterprise AI Workflows: Integrate LLMs with internal tools for real-time decision-making systems.
2. Multi-Tool Orchestration: Connect LLMs to databases, APIs, or IoT devices through reusable routers.
3. Scalable Development: Rapidly prototype new capabilities by adding custom routers without infrastructure reconfiguration.
4. Production-Ready Deployments: Manage logging, error handling, and resource allocation at enterprise scale.

MCP SSE Server (mcp-ectors) FAQ

FAQ from MCP SSE Server (mcp-ectors): Scalable Real-Time AI Infrastructure?

  • Why Rust? - Leverages memory safety and performance for critical infrastructure workloads.
  • Can I extend transport protocols? - Future versions will add stdio and WASI support; community contributions are encouraged.
  • How does router management work? - Routers are dynamically registered into a centralized service manager, ensuring seamless request routing.
  • What’s the roadmap? - Priorities include OAuth integration, notifications, and enhanced security features.

Content

MCP SSE Server (mcp-ectors)

The MCP SSE Server , or mcp-ectors for short, is an enterprise-ready, high-performance server designed to enable seamless integration and interaction between large language models (LLMs) and various tools, resources, and workflow prompts. This powerful server acts as the bridge, much like a USB interface, for LLMs to gain access to multiple capabilities, enabling agents and agentic AI. Built using Rust and actors , it is optimized for performance and scalability, making it a great fit for enterprise environments.

Note : The name mcp-ectors comes from "MCP Enterprise Actors Server", and has nothing to do with the creator's last name, despite how it might sound 😉

Key Features

  • High Performance : Built with actors and Rust , the server ensures high scalability and concurrency.
  • MCP as the USB for LLMs : Enables access to tools, resources, and workflow prompts through a clean API.
  • Reuse Connections : Unlike other MCP servers, mcp-ectors allows multiple routers to be deployed on the same connection, simplifying architecture and resource management.
  • Multiple Routers : Register multiple routers and utilize them dynamically through the Router Service Manager.

Getting Started

Prerequisites

To get started with mcp-ectors, make sure you have the following installed:

  • Rust (via rust-lang)
  • Cargo (comes with Rust)
  • Cargo run for running the application.

Running the Server

  1. Clone the repository :

    git clone https://github.com/yourusername/mcp-ectors.git

cd mcp-ectors
  1. Run the server : After cloning the repository, navigate to the project folder and run the server with:

    cargo run

The server will start on http://localhost:8080/sse.

  1. Start with the Goose Desktop : In Goose Desktop (a companion tool), you can add extensions, choose SSE as the transport, and use the following URL:

    http://localhost:8080/sse

Using the Counter Example

  1. After running the server, in the Goose Desktop application you can ask to increment the counter or get the current value.

  2. Try also Hello World greet.

Create New MCP Routers

MCP-ectors enables you to create and register new routers through the Router Trait. To add a new router, implement the Router trait for your new router, following the examples of the existing CounterRouter or HelloWorldRouter.

Example:

use mcp_ectors::router::Router;

pub struct MyNewRouter;

impl Router for MyNewRouter {
    fn handle_request(&self, request: Request) -> Response {
        // Implement your router's logic here
    }
}

Registering Routers

In MCP , tools, resources, and prompts are registered as routerid_tool, routerid_prompt, and routerid_resource to keep everything well-organized. The Router Service Manager allows these elements to be dynamically added.

Example Registration:

let counterid = "counter".to_string();
let counter_router = Box::new(CounterRouter::new());
router_manager.register_router::<CounterRouter>(counterid, counter_router).await.expect("router could not be registered");

let hwid = "helloworld".to_string();
let hw_router = Box::new(HelloWorldRouter::new());
router_manager.register_router::<HelloWorldRouter>(hwid, hw_router).await.expect("router could not be registered");

Architecture Overview

  1. Server Builder :
* The `server_builder` determines the transport layer. Currently, **SSE** is supported. Future versions will include **stdio** and **wasi** transport.
* For now, the server supports **SSE** for communication between the client and the server.
  1. Router Service Manager :
* The `RouterServiceManager` is responsible for registering multiple routers and ensuring that each router can handle requests without the need for new connections.
* This architecture allows you to deploy several routers with the same connection, making the system highly efficient and scalable.
  1. Log Configuration :
* The server can be configured to store logs in specific directories and set custom log levels for monitoring and debugging.
* The configuration can be customized using the `LogConfig` struct.
  1. Transport Actor :
    Any transport used in the MCP server needs to implement the transport actor. The TransportActorTrait ensures that transports handle requests and messages correctly:
* **TransportRequest** : Allows new `JsonRPCMessages` to be sent to the client. It is used for communication between the server and the client through the transport layer.
* **StartTransport** : This message starts the transport, initializing any necessary background tasks, such as setting up connections or waiting for incoming messages.
* **StopTransport** : This message stops the transport, gracefully shutting down any active connections or tasks tied to the transport layer.
  1. Router :
    The Router is a trait that any router needs to implement, closely linked to the MCP standard. The RouterServiceManager uses the RouterRegistry to register new routes. New routes are embedded inside a RouterActor , which manages the communication for specific functionality. For instance, when a tools/call request is made, the actor holding the router will respond with the appropriate action. This setup allows the server to dynamically respond to a variety of requests by leveraging multiple routers.

  2. Standard Actors :
    MCP has a set of standard actors that implement basic functions such as initialization and managing tools, prompts, and resources. These standard actors are responsible for handling initialization requests and responding to list requests for tools, prompts, and resources. This makes it easier to interact with these essential components, providing a uniform and standardized method of retrieving and managing the core assets across different routers.

Example Log Configuration:

let log_config = LogConfig {
    log_dir: "logs".to_string(),
    log_file: "server.log".to_string(),
    level: Level::INFO,
};

Future Development

  • MCP Protocol : The basics have been implemented but notifications are still missing. Also oAuth, secrets management,... are on the roadmap.
  • Transport Extensions : Currently, the server supports SSE transport, with plans to add stdio and wasi in the future.
  • Help Wanted : Contributions are welcome! If you have expertise in other transports like WASI or stdio , feel free to submit a PR.

Conclusion

The MCP SSE Server (mcp-ectors) is built for high performance, scalability, and ease of use. With actors , Rust , and a clean architecture for managing multiple routers, it makes working with LLMs, tools, and resources effortless. Whether you're a researcher, developer, or AI enthusiast, mcp-ectors will help you integrate LLMs with the tools and resources you need for advanced agentic AI workflows.


Feel free to contribute , test , and expand the system for your enterprise use cases. You can rely on mcp-ectors to power your next-generation AI applications. If your company wants to create custom routers or partner, please reach out to Maarten Ectors.

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