asyncmcp - Async transport layers for MCP
Overview
A regular MCP Server but working over queues :
queue-based-mcp-example.mov
Quoting from the official description :
MCP is an open protocol that standardizes how applications provide context to LLMs.
But a lot of this context is not always readily available and takes time for the applications to process - think batch processing APIs, webhooks or queues. In these cases with the current transport layers, the MCP server would have to expose a light-weight polling wrapper in the MCP layer to allow waiting and polling for the tasks to be done. Although SSE does provide async functionalities but it comes with caveats.
asyncmcp explores supporting more of the async transport layer implementations for MCP clients and servers, beyond the officially supported stdio and Streamable Http transports.
The whole idea of an MCP server with async transport layer is that it doesn't have to respond immediately to any requests. It can choose to direct them to internal queues for processing and the client doesn't have to stick around for the response.
Current capabilities
Transport layer : sns-sqs
Server : Transport layer that listens to a queue for MCP requests and writes the responses to a topic
Client : Transport layer that writes requests to a topic and listens to a queue for responses
Installation and Usage
# Using uv (recommended) uv add asyncmcp
# Using pip pip install asyncmcp
Basic server setup
Note : we don't support FastMCP yet. The examples in this repo uses the basic way of creating MCP servers and client
Here's a basic example of implementing an MCP server which supports sns-sqs as the transport layer:
import boto3 from asyncmcp . sns_sqs . server import sns_sqs_server from asyncmcp import SnsSqsTransportConfig # Configure transport config = SnsSqsTransportConfig ( sqs_queue_url = "https://sqs.region.amazonaws.com/account/service-queue" , sns_topic_arn = "arn:aws:sns:region:account:mcp-responses" ) # more configurable params available. # Create AWS clients sqs_client = boto3 . client ( 'sqs' ) sns_client = boto3 . client ( 'sns' ) async def main (): async with sns_sqs_server ( config , sqs_client , sns_client ) as ( read_stream , write_stream ): # Your MCP server logic here pass
Basic client setup
Here's a basic example of implementing an MCP client which supports sns-sqs as the transport layer:
import boto3 from asyncmcp . sns_sqs . client import sns_sqs_client from asyncmcp import SnsSqsTransportConfig # Configure transport config = SnsSqsTransportConfig ( sqs_queue_url = "https://sqs.region.amazonaws.com/account/client-queue" , sns_topic_arn = "arn:aws:sns:region:account:mcp-requests" ) # more configurable params available. # Create AWS clients sqs_client = boto3 . client ( 'sqs' ) sns_client = boto3 . client ( 'sns' ) async def main (): async with sns_sqs_client ( config , sqs_client , sns_client ) as ( read_stream , write_stream ): # Your MCP client logic here pass
You can check full examples at /examples/website_server.py and /examples/website_client.py .
Read more at /examples/README.md
Limitations
Message Size : For SQS - message size limits are applicable (256KB standard, 2MB extended)
: For SQS - message size limits are applicable (256KB standard, 2MB extended) Response Handling : Async nature means responses may not be immediate
: Async nature means responses may not be immediate Session Context : Storage mechanism handled by server application, not transport
: Storage mechanism handled by server application, not transport Ordering: Standard SQS doesn't guarantee message ordering
Testing
Unit Tests
uv run pytest
Contributing
We welcome contributions and discussions about async MCP architectures!
Development Setup
git clone https://github.com/bharatgeleda/asyncmcp.git cd asyncmcp uv sync
License
Apache License 2.0 - see LICENSE file for details.
Links