Galaxy MCP vs Candor

A side-by-side look at the Galaxy MCP and Candor MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

Galaxy MCP logoGalaxy MCPBiology & Bioinformatics · Local subprocess (stdio)MCP server for Galaxy bioinformatics platform - connect, execute tools, and manage workflows61GoodAuth: not declaredCandor logoCandorBiology & Bioinformatics · Local subprocess (stdio)Per-function effect analysis for agents: blast radius, what reaches the network, gate verdicts.45FairAuth: not declared

Verdict: choose Galaxy MCP for biology & bioinformatics work as a local process; choose Candor for biology & bioinformatics as a local process. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

Galaxy MCP logoChoose Galaxy MCP when

  • You need dedicated capabilities in the Biology & Bioinformatics domain.
  • You prefer a local stdio subprocess transport.
  • You want tools like connect, search_tools_by_name, get_tool_details.
Explore Galaxy MCP

Candor logoChoose Candor when

  • You need dedicated capabilities in the Biology & Bioinformatics domain.
  • You prefer a local stdio subprocess transport.
Explore Candor

Feature & specification comparison

Rows where the two servers differ are marked.

SpecGalaxy MCP logoGalaxy MCPCandor logoCandor
CategoryBiology & BioinformaticsBiology & Bioinformatics
Quality signal61/100 · Good45/100 · Fair
Install commandConfirmedConfirmed
TransportLocal subprocess (stdio)Local subprocess (stdio)
AuthNot declaredNot declared
PricingNot declaredNot declared
Required env varsNone listedNone listed
Verified ownerCommunity listingCommunity listing
GitHub stars391
Directory activity 1 views 0 installs 0 upvotes 2 views 0 installs 0 upvotes
Tools48Not listed

Tools & capabilities

Galaxy MCP tools 48

  • connectConnect to Galaxy server
  • search_tools_by_nameSearch Galaxy tools whose name, ID, or description contains the given query (substring match). Results are paginated. pagination.total_items is how many tools matched in total; pagination.next_offset is where the next page starts (None on the last page). RECOMMENDED WORKFLOW: 1. Use this function to find tools by name/keyword 2. Review the returned tool IDs and names 3. Call get_tool_details(tool_id) for full input parameters 4. Call run_tool() with the correct inputs
  • get_tool_detailsGet detailed information about a specific tool including its input parameters. RECOMMENDED WORKFLOW: 1. First find tools using search_tools_by_name() or get_tool_panel() 2. Call this function with io_details=True to see all input parameters 3. Use the inputs schema to construct the inputs dict for run_tool()
  • get_tool_run_examplesReturn the exact XML test definitions (inputs, outputs, assertions, required files) for a Galaxy tool so an LLM can study real, working run configurations.
  • get_tool_input_templateReturn a ready-to-fill ``inputs`` skeleton for a tool, plus a compact schema. Call this before run_tool when you are unsure how to shape ``inputs``. Replace placeholders (e.g. ``<dataset_id>``) with real values. Repeats show one instance (``name_0|...``); duplicate with ``name_1|...`` to add more. The flattened-key convention is ``section|param``, ``cond|selector``, ``repeat_0|param``.
  • get_tool_citationsGet citation information for a specific tool
  • run_toolRun a Galaxy tool on datasets in a history. RECOMMENDED WORKFLOW: 1. Create or select a history: create_history() or get_histories() 2. Upload data: upload_file() or upload_file_from_url() 3. Get tool parameters: get_tool_details(tool_id, io_details=True) 4. Call this function with properly formatted inputs 5. Monitor job: get_job_details() or check history contents
  • get_tool_panelBrowse the Galaxy tool panel (toolbox) one level at a time. The whole panel is megabytes on a production server, so it is never returned whole. Called with no arguments this lists the top-level entries - each section with the number of tools in it, plus any tools that sit outside a section. Pass section_id to list the tools in one section.
  • create_historyCreate a new history to organize datasets and analyses. A history is the primary workspace in Galaxy. Create a new history for each distinct project or analysis to keep your work organized. RECOMMENDED WORKFLOW: 1. Create a history with a descriptive name 2. Upload your input data: upload_file() or upload_file_from_url() 3. Run tools on the data: run_tool() 4. View results: get_history_contents()
  • update_historyUpdate an existing Galaxy history's metadata. Any combination of name, annotation, tags, deleted, and published can be updated in a single call. Fields left as None are not modified.
  • search_tools_by_keywordsRecommend Galaxy tools based on a list of keywords. Matches on name and description first, then on accepted input formats, and keeps that order so paging is stable. Results are paginated: pagination.total_items is the full match count, pagination.next_offset is where the next page starts. Expensive: finding the format matches costs one detail lookup per tool that did not match by name, and every page repeats the whole scan. Prefer search_tools_by_name when a name or description substring will do.
  • get_server_infoGet Galaxy server information including version, URL, and configuration details Also reports which tools this server is too old to run, in `unsupported_tools`, and whether its version could be read at all, in `version_known` -- an empty `unsupported_tools` means nothing is ruled out only when `version_known` is true. Returns: GalaxyResult with server information in data field
  • +36 more on the listing page

Candor tools

No tool names declared yet. Check the project README from the listing page.

Ready-to-paste client configs

Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.

Galaxy MCP

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "galaxy-mcp": {
      "command": "uvx",
      "args": [
        "galaxy-mcp"
      ]
    }
  }
}

Candor

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "candor": {
      "command": "npx",
      "args": [
        "-y",
        "candor-ts"
      ]
    }
  }
}

Frequently asked questions

Galaxy MCP is categorized under Biology & Bioinformatics and uses a local stdio subprocess. Candor belongs to Biology & Bioinformatics and uses a local stdio subprocess. Pick Galaxy MCP for biology & bioinformatics work and Candor for biology & bioinformatics.

Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.

Galaxy MCP has no declared pricing — check the project's own site. Candor has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.

Yes. MCP clients support multiple servers: add galaxy-mcp and candor as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, Galaxy MCP has a quality signal of 61/100 (Good) with 1 views, 0 installs and 39 GitHub stars. Candor has 45/100 (Fair) with 2 views, 0 installs and 1 GitHub stars.