Galaxy MCP server
io.github.galaxyproject/galaxy-mcp·v1.3.0·39 starsMCP server for Galaxy bioinformatics platform - connect, execute tools, and manage workflows
39 stars
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Galaxy tools (31, 6 write)
write = sends, deletes, buys or postsRead from the package source without running it. The installed server may list more.
cancel_workflow_invocationwrite actionCancel a running workflow invocation
connectConnect to Galaxy server
create_historywrite actionCreate a new history to organize datasets and analyses.
download_datasetDownload a dataset from Galaxy to the local filesystem or memory
get_collection_detailsGet detailed information about a dataset collection and its members
get_dataset_detailsGet detailed information about a specific dataset, optionally including a content preview
get_historiesGet list of user's histories with optional pagination and filtering.
get_history_contentsGet paginated contents (datasets and collections) from a specific history with ordering support
get_history_detailsGet history metadata and summary count ONLY - does not return actual datasets
get_invocationsView workflow invocations in Galaxy
get_iwc_workflow_detailsGet comprehensive details about a specific IWC workflow before importing.
get_iwc_workflowsFetch all workflows from the IWC (Interactive Workflow Composer)
get_job_detailsGet detailed information about the job that created a specific dataset
get_server_infoGet Galaxy server information including version, URL, and configuration details
get_tool_citationsGet citation information for a specific tool
get_tool_detailsGet detailed information about a specific tool including its input parameters.
get_tool_panelGet the tool panel structure (toolbox)
get_tool_run_exampleswrite actionReturn the exact XML test definitions (inputs, outputs, assertions, required files) for a Galaxy tool so an LLM can study real, working run configurations.
get_userGet current user information
get_workflow_detailsGet detailed information about a specific workflow
import_workflow_from_iwcImport a workflow from IWC to the user's Galaxy instance
invoke_workflowInvoke (run) a workflow with specified inputs and parameters
list_history_idsGet a simplified list of history IDs and names for easy reference
list_workflowsList workflows available in the Galaxy instance
recommend_iwc_workflowsSemantic search for IWC workflows based on natural language description.
run_toolwrite actionRun a Galaxy tool on datasets in a history.
search_iwc_workflowsSearch for workflows in the IWC (Intergalactic Workflow Commission) manifest.
search_tools_by_keywordsRecommend Galaxy tools based on a list of keywords.
search_tools_by_nameSearch Galaxy tools whose name, ID, or description contains the given query (substring match).
upload_filewrite actionUpload a local file to Galaxy for analysis.
upload_file_from_urlwrite actionUpload a file from a URL to Galaxy
Public scan report
scanner v0.1.10 · 2026-09-28 · same rubric, same numbers if you re-run it
- Code scan5 source files scanned25/25
- –Live reliabilityno gateway calls yet and no remote to proben/a
- –Tool poisoningtools not inspected (local package is not executed); not countedn/a
- Auth qualitystatic API keys via environment variables6/15
- Maintenancelast push 0 days ago15/15
- Maintainer identityregistry namespace matches repository owner; GitHub account older than a year9/10
How Galaxy compares
Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 85/100
- higher than 70% of 48,255 servers
- Tools
- 31
- the typical server has 7
- Tools that change things
- 19%
- typical: 0%. Fewer write tools means less an agent can break
- GitHub stars
- 39
- more than 93% of 28,688 servers
What its tools let an agent do: 23 read · 4 create · 1 change · 1 delete · 2 run or deploy
Install Galaxy in Claude Code, Cursor or VS Code
claude mcp add galaxy-mcp -- uvx galaxy-mcp
What the publisher says
From the Galaxy repository's README, as published. We do not edit it. Read it on GitHub
Galaxy MCP Server
This project provides a Model Context Protocol (MCP) server for interacting with the Galaxy bioinformatics platform. It enables AI assistants and other clients to connect to Galaxy instances, search and execute tools, manage workflows, and access other features of the Galaxy ecosystem.
Project Overview
The repository holds two independent implementations of the same Galaxy operation set:
PyPI as galaxy-mcp. It reaches Galaxy through BioBlend and carries the larger tool surface. See the Python README.
- mcp-server-galaxy-py/ -- the Python MCP server, published to
same operations two ways: a galaxy-cli command-line tool and a galaxy-mcp (Node) MCP server, both built on a shared framework-free core. See the galaxy-agent-tools README.
- galaxy-agent-tools/ -- a TypeScript pnpm workspace offering the
The two are meant to stay in step: an operation keeps its name and its meaning across both. They are still separate codebases with separate release trains, though, so each README lists the operations that surface actually has -- read the one you are using.
Key Features
- Galaxy Connection: Connect to any Galaxy instance with a URL and API key
- OAuth Login (optional): Offer browser-based sign-in that exchanges credentials for temporary Galaxy API keys
- Server Information: Retrieve comprehensive server details including version, configuration, and capabilities
- Tools Management: Search the tool catalog, inspect a tool's inputs, and execute Galaxy tools
- User-Defined Tools: Create, list, run, and deactivate unprivileged user-defined tools
- Workflow Integration: Find and import workflows from the Intergalactic Workflow Commission (IWC), then invoke them and follow their invocations
- History Operations: Manage Galaxy histories, datasets, and collections, and inspect the jobs behind them
- File Management: Upload files to Galaxy from local storage or from a URL, and download results back
- Pages: Read and write Galaxy-flavored markdown pages -- history-attached notebooks and standalone reports -- including their revision history
- Verified Container Recommendation (optional): Resolve a real quay.io/biocontainers image for a set of conda packages instead of guessing one -- see Optional extras
- Mock-based test suite: The default suite runs entirely against mocked Galaxy responses, so it needs no server; a separate suite against a live Galaxy is opt-in and skips when no credentials are configured
Optional extras
container-recommend
Enables the recommendbiocontainer tool, which resolves a verified quay.io/biocontainers image for a set of conda packages. Authoring a user-defined tool means naming a container, and a hallucinated image tag is the most common way a UDT passes validation and then dies at run time with manifest unknown. This wraps galaxy.toolutil.deps.mulled.recommend -- the same resolver Galaxy's own custom-tool agent uses (added in Galaxy 26.1, galaxyproject/galaxy#22981) -- so the image is checked against quay.io rather than invented.
It is an extra rather than a hard dependency because galaxy-tool-util pulls in lxml and conda-package-streaming, and every other tool on this server works without it. The tool is only registered when the extra is installed, so a stock install simply doesn't advertise it.
uvx --from 'galaxy-mcp[container-recommend]' galaxy-mcp
# or, for a local checkout:
cd mcp-server-galaxy-py && uv sync --extra container-recommendThe same resolver is also available as a standalone CLI once installed: mulled-recommend samtools=1.17.
code-mode
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Galaxy: common questions
- Is Galaxy MCP server safe?
- Yes, by our scan: it is graded A (85/100). Read the Galaxy safety report
- How do I install Galaxy?
- It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
- Does Galaxy need an API key?
- Yes. The registry entry asks for
GALAXY_API_KEY. - Is Galaxy maintained?
- The last commit was 37 days ago (2026-09-28). The latest release is v1.3.0.
- How does Galaxy compare with other MCP servers?
- safety score 85/100 (higher than 70% of 48,255 servers); tools 31 (the typical server has 7); tools that change things 19% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.