Galaxy Mcp
Drive Galaxy workflows, execute bioinformatics tools, and manage histories from your agent when building reproducible analysis pipelines.
Overview
Galaxy MCP is a Build-phase MCP server that connects AI assistants to Galaxy to execute bioinformatics tools and manage workflows via API key auth.
What is this MCP server?
- PyPI galaxy-mcp v1.3.0 stdio MCP server for the Galaxy bioinformatics platform
- GALAXY_URL and GALAXY_API_KEY required for instance auth (e.g. usegalaxy.org)
- Connect, execute Galaxy tools, and manage workflows via agent-callable tools
- Official galaxyproject/galaxy-mcp repository on GitHub
- Suited to reproducible pipeline orchestration rather than one-off spreadsheet analysis
- PyPI galaxy-mcp version 1.3.0 per server.schema.json
- Stdio transport; 2 required env vars (GALAXY_URL, GALAXY_API_KEY)
- Repository source galaxyproject/galaxy-mcp on GitHub
What problem does it solve?
Bioinformatics solo builders lose reproducibility when every Galaxy job is manual UI work and the agent cannot see or trigger workflows on your instance.
Who is it for?
Indie bioinformatics or computational biology builders who already use Galaxy and want agent-assisted pipeline runs from Claude Code or Cursor.
Skip if: General web app backends with no Galaxy account, or teams needing wet-lab LIMS instead of workflow orchestration APIs.
What do I get? / Deliverables
After MCP registration your agent can operate Galaxy connect, tool run, and workflow management tools against your configured instance.
- Agent-triggered Galaxy tool runs and workflow operations
- Authenticated MCP bridge to your Galaxy deployment
- Stdio registration for reproducible analysis automation
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Journey fit
Galaxy connection is a Build-time integration for computational workflows before you treat results as growth or ops telemetry. Integrations fits external platform APIs—here Galaxy instance URL and API key—for tool execution and workflow management.
How it compares
Galaxy platform MCP connector—not a local CLI for BLAST or a generic ETL skill.
Common Questions / FAQ
Who is Galaxy MCP for?
Developers and researchers using Galaxy who want MCP-driven tool execution and workflow management inside AI coding agents.
When should I use Galaxy MCP?
During Build integrations while wiring reproducible analysis pipelines and iterating jobs on a Galaxy server you control or share.
How do I add Galaxy MCP to my agent?
Install galaxy-mcp from PyPI, set GALAXY_URL and GALAXY_API_KEY, register the stdio server in your MCP client, then invoke workflow and tool resources from chat.