asya
Verified Safeby deliveryhero
Overview
A microservices platform for orchestrating asynchronous, event-driven AI/ML workflows via an MCP JSON-RPC gateway.
Installation
export ASYA_DATABASE_URL="postgresql://user:pass@localhost:5432/asyaEnvironment Variables
- ASYA_CONFIG_PATH
- ASYA_DATABASE_URL
- ASYA_GATEWAY_PORT
- ASYA_RABBITMQ_URL
- ASYA_RABBITMQ_EXCHANGE
- ASYA_SQS_ENDPOINT
- ASYA_SQS_REGION
- ASYA_NAMESPACE
- ASYA_ACTOR_NAME
- ASYA_SOCKET_DIR
- ASYA_RUNTIME_TIMEOUT
- ASYA_GATEWAY_URL
- ASYA_LOG_LEVEL
- ASYA_METRICS_ENABLED
- ASYA_METRICS_ADDR
- ASYA_METRICS_NAMESPACE
- ASYA_CUSTOM_METRICS
- ASYA_IS_END_ACTOR
- ASYA_HANDLER
- ASYA_HANDLER_MODE
Security Notes
The system relies on external message brokers (RabbitMQ/SQS) and a PostgreSQL database. Default RabbitMQ credentials ('guest:guest') are used if not overridden, posing a risk in production environments. AWS SQS credentials are expected from secrets or IRSA, which is a good practice. Actor runtimes execute Python code, which implies trust in the deployed actor code. The HTTP/SSE endpoints on the gateway perform input validation and use `json.Marshal` for SSE data to mitigate XSS risks. No direct 'eval' or obfuscation found, and inter-service communication over Unix sockets is generally secure.
Similar Servers
mcp_massive
An AI agent orchestration server, likely interacting with LLMs and managing multi-agent workflows.
AgentUp
A developer-first framework for building, deploying, and managing AI agents, bringing Docker-like consistency and operational ease to AI agent development.
AgentUp
A developer-first framework for building, deploying, and managing secure, scalable, and configurable AI agents, supporting various agent types (reactive, iterative) and the Model-Context Protocol (MCP) for seamless interactions.
ironmanus-mcp
Orchestrates AI workflows with an 8-phase control flow and specialized tools, serving as a Model Context Protocol (MCP) server.