Poiesis MCP Server
Provides access to containerized computational task execution through GA4GH Task Execution Service (TES), enabling creation, monitoring, and management of Docker-based computational workflows
Enables seamless access to GA4GH Task Execution Service (TES) functionality for creating, monitoring, and managing computational tasks through a TES-compliant service
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Poiesis MCP Serverrun a BLAST analysis on my genome sequence file"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Poiesis MCP Server
A Model Context Protocol (MCP) server that provides seamless access to GA4GH Task Execution Service (TES) functionality. This server enables AI assistants and LLMs to create, monitor, and manage computational tasks through a TES-compliant service.
Prerequisites
Access to a GA4GH TES-compliant service, Check out Poiesis.
MCP clients like Claude, Gemini etc.
Related MCP server: Google Tasks MCP Server
Installation
TBA.
tl;dr: Either install poiesis_mcp or use its Docker image to start the server.
Configuration
Configure the server using environment variables:
Required Configuration
TES_URL: The base URL of your TES service (e.g.,https://tes.example.com)TES_TOKEN: Authentication token for the TES service
Optional Configuration
TES_REQUEST_TIMEOUT: HTTP request timeout in seconds (default: 60)TES_MAX_RETRIES: Maximum number of retry attempts (default: 3)TES_BACKOFF_FACTOR: Backoff factor for retries (default: 1.0)MCP_HOST: Server host address (default: 0.0.0.0)MCP_PORT: Server port number (default: 8080)LOG_LEVEL: Logging level - DEBUG, INFO, WARNING, ERROR (default: INFO)TASK_POLL_INTERVAL: Polling interval for task monitoring in seconds (default: 5)TASK_POLL_MAX_ATTEMPTS: Maximum polling attempts (default: 120)
This server cannot be deployed
Maintenance
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