Workflows & Templates

The ivybloom CLI is the scriptable surface for the platform, and workflows are where you turn a sequence of tools into a single automated pipeline — each step's output feeding the next without manual intervention. Reach for workflow templates when you want a reproducible, multi-step drug discovery pipeline you can list, manage, and execute from scripts or CI/CD rather than driving each tool by hand. For the full command surface, see the CLI overview.

Workflows & Templates

Build and execute multi-step automated pipelines with workflow templates.

Overview

A workflow is a YAML or JSON file that lists jobs, their parameters and their depends_on order. The CLI generates the file, validates it and runs it. Each job can read an earlier job's output (for example structure_source: job1.output).

Workflow Files

Create a Workflow File

ivybloom workflows create my_pipeline.yaml
ivybloom workflows create my_pipeline.json --format json

The generated file looks like this:

name: My Workflow
description: Description of what this workflow does
version: "1.0"
jobs:
    - id: job1
      name: First Job
      tool: esmfold
      parameters:
        sequence: MKFLILLFNILCLFPVLAADNHGVGPQGAS
    - id: job2
      name: Second Job
      tool: docking
      parameters:
        ligand_source: uploaded_file.sdf
        structure_source: job1.output
      depends_on:
        - job1
options:
    parallel: false
    on_failure: stop
    timeout: 3600
    max_retries: 2
    retry_delay: 60

Validate a Workflow File

ivybloom workflows validate my_pipeline.yaml

Workflow Templates

List Available Templates

ivybloom workflows templates
ivybloom workflows templates --category discovery

Categories: discovery, optimization, design, assessment, synthesis.

View Template Details

ivybloom workflows template TEMPLATE_ID

Shows the template's parameter schema, steps, dependencies and estimated duration.

Listing Workflows

ivybloom workflows list
ivybloom workflows list --format json

The CLI command has no project filter. The workflows_list MCP tool accepts an optional project_id.

Executing Workflows

From the CLI

# Show the execution plan without running
ivybloom workflows run my_pipeline.yaml --dry-run

# Run, wait for every job, and attach to a project
ivybloom workflows run my_pipeline.yaml --wait --project-id PROJECT_ID

# Run independent jobs in parallel
ivybloom workflows run my_pipeline.yaml --parallel

Via MCP

ivybloom mcp serve exposes workflow tools to AI agents: workflows_list, workflows_get, workflows_create, workflows_execute, workflows_results, workflows_templates and workflows_template_get.

MCP tool: workflows_execute
Parameters: workflow_id (required), inputs, parameters

Via Orchestration

Use natural language to trigger multi-step work:

ivybloom orchestrate "Fold EGFR, find binding sites, and dock erlotinib"

The orchestrator chains the tools it picks. See Orchestration for details.

Workflow Results

Per-workflow details and step results are available through the workflows_get and workflows_results MCP tools. The CLI has no workflows get or workflows results subcommand; use ivybloom jobs list and ivybloom jobs download JOB_ID for the jobs a run submitted.

Pipeline Examples

Structure-Based Drug Discovery

High-Throughput Screening

See Recipes for step-by-step walkthroughs of these pipelines.

Read next

• Orchestration — Natural language workflow execution
• Batch Processing — Parallel job collections
• MCP Integration — AI agent workflow execution
• Recipes — Step-by-step workflow tutorials
• Commands Reference — Full command documentation