Documentation Index Fetch the complete documentation index at: https://docs.crewship.dev/llms.txt
Use this file to discover all available pages before exploring further.
Overview The crewship.toml file configures how your crew is built and deployed. Place it in your project root.
Crewship supports two formats:
Single deployment — one [deployment] section (default, created by crewship init)Multi-deployment — multiple [deployments.<name>] sections for monorepos with several agents
Run crewship init Single Deployment (default) CrewAI
LangGraph
LangGraph.js
[ deployment ] framework = "crewai" entrypoint = "src.my_crew.crew:MyCrew" profile = "slim" python = "3.11" [ build ] exclude = [ "tests" ]
[ deployment ] framework = "langgraph" entrypoint = "src.my_agent.graph:graph" profile = "slim" python = "3.11" [ build ] exclude = [ "tests" ]
[ deployment ] framework = "langgraph-js" entrypoint = "./src/graph.ts:graph" profile = "slim" [ build ] exclude = [ "tests" ]
Multi-Deployment For monorepos with multiple agents sharing the same codebase, use named [deployments.<name>] sections:
[ build ] exclude = [ "tests" ] [ deployments . research-agent ] framework = "crewai" entrypoint = "research_crew.crew:ResearchCrew" profile = "slim" python = "3.11" [ deployments . writer-agent ] framework = "crewai" entrypoint = "writer_crew.crew:WriterCrew"
Each named deployment gets its own deployment on Crewship with the name as the project name (e.g. research-agent).
[apis] and [chat] can be set at the top level as global defaults, and overridden per deployment:# Global defaults [ chat ] input_key = "query" [ deployments . support-agent ] framework = "crewai" entrypoint = "support_crew.crew:SupportCrew" [ deployments . research-agent ] framework = "crewai" entrypoint = "research_crew.crew:ResearchCrew" # Override chat config for this deployment only [ deployments . research-agent . chat ] input_key = "topic"
[deployment] and [deployments.*] are mutually exclusive. Using both in the same file will produce an error.
Selecting a deployment Use --name / -n on any command to target a specific deployment:
crewship deploy --name research-agent crewship invoke --name writer-agent --input '{"topic": "AI"}' crewship env set --name research-agent OPENAI_API_KEY=sk-...
If --name is omitted:
One named deployment — auto-selectedMultiple named deployments — interactive prompt (or error in CI)Single [deployment] format — used directly (no --name needed)
Deployment IDs After the first deploy, deployment_id is saved into each section automatically:
[ deployments . research-agent ] framework = "crewai" entrypoint = "research_crew.crew:ResearchCrew" deployment_id = "dep_xxx1" # auto-populated [ deployments . writer-agent ] framework = "crewai" entrypoint = "writer_crew.crew:WriterCrew" deployment_id = "dep_xxx2" # auto-populated
Full Example [ deployment ] framework = "crewai" entrypoint = "src.research_crew.crew:ResearchCrew" python = "3.11" profile = "slim" [ build ] exclude = [ "tests" ] [ build . install ] packages = [ "ffmpeg" , "imagemagick" ] [ apis ] enabled = [ "thread" , "run" ] [ chat ] input_key = "topic" [ runtime ] timeout = 600 memory = 512 [ metadata ] description = "A crew that researches topics and writes reports" tags = [ "research" , "writing" ]
Configuration Reference [deployment] / [deployments.<name>] Field Type Required Description frameworkstring ✅ Framework to use: crewai, langgraph, or langgraph-js entrypointstring ✅ Entry point for your agent (format varies by framework) pythonstring "3.11"Python version (3.10, 3.11, 3.12) — Python frameworks only profilestring "slim"Base image profile dockerfilestring — Custom Dockerfile path deployment_idstring — Auto-populated after first deploy
Entrypoint Format The entrypoint format depends on your framework:
CrewAI and LangGraph (Python) — Python module path:module.path:ClassName_or_variable
# CrewAI: points to a class decorated with @CrewBase entrypoint = "src.my_crew.crew:MyCrew" # LangGraph: points to a compiled graph variable entrypoint = "src.my_agent.graph:graph"
LangGraph.js — file path relative to project root:./path/to/file.ts:exportName
# LangGraph.js: points to an exported compiled graph entrypoint = "./src/graph.ts:graph"
Run crewship init to auto-detect your framework and entrypoint. For LangGraph projects, place a langgraph.json in your project root to enable auto-detection.
Profile Options Profile Description Frameworks Use case slimMinimal base environment All Most agents browserIncludes Playwright + Chromium crewai, langgraphWeb scraping, screenshots
[build] Build configuration options.
Field Type Default Description excludearray of string []Paths to exclude from build
[build.install] Additional system packages to install.
[ build . install ] packages = [ "ffmpeg" , "poppler-utils" , "tesseract-ocr" ]
Only packages available in the base image’s package manager (apt) are supported.
[runtime] Runtime configuration.
Field Type Default Description timeoutinteger 300Max execution time in seconds memoryinteger 256Memory limit in MB
[ runtime ] timeout = 900 # 15 minutes memory = 1024 # 1 GB
[apis] Controls which APIs are enabled for the deployment. This affects both direct API access and which interaction modes are available in Slack .
Field Type Default Description enabledarray of string — Which APIs to expose: "thread", "run"
When omitted (or null), all APIs are enabled by default.
[ apis ] enabled = [ "thread" , "run" ] # Both APIs enabled (same as default)
[ apis ] enabled = [ "run" ] # Only stateless runs — no thread/conversation support
[ apis ] enabled = [ "thread" ] # Only threaded conversations — no standalone runs
In Slack, the enabled APIs determine which interaction modes work:
Thread API — @mention conversations use threads for multi-turn contextRun API — /crewship run slash commands use single stateless runsIf both are enabled, @mention defaults to thread mode
Not sure which to use? Read Runs vs Threads: When to Use Which . [chat] Configures how chat messages (from Slack or other integrations) map to your crew’s input and output.
Field Type Default Description input_keystring "input"The parameter name that receives the chat message output_keystring — Field in the run output containing response messages
[ chat ] input_key = "topic"
When a user sends a message in Slack (e.g. “Tell me about quantum computing”), it gets mapped to:
{ "topic" : "Tell me about quantum computing" }
If output_key is set, the platform extracts that field from the run result to display as the response:
[ chat ] input_key = "query" output_key = "messages"
If your crew already accepts an input parameter, you can omit [chat] entirely — it defaults to input_key = "input".
Optional metadata for organization.
Field Type Description descriptionstring Human-readable description tagsarray Tags for filtering in Console
[ metadata ] description = "Researches topics and generates blog posts" tags = [ "content" , "blog" , "research" ]
Validation The CLI validates your crewship.toml on deploy:
Common validation errors:
❌ Error: Invalid crewship.toml - name: must be lowercase with hyphens only - deployment.entrypoint: required field missing
Environment-specific Config For different environments, use separate projects:
# Production crewship deploy --project my-crew # Staging crewship deploy --project my-crew-staging
Set different environment variables per project:
crewship env set OPENAI_API_KEY=sk-prod-... --project my-crew crewship env set OPENAI_API_KEY=sk-test-... --project my-crew-staging
Example Configurations Basic CrewAI [ deployment ] framework = "crewai" entrypoint = "src.simple_crew.crew:SimpleCrew"
Basic LangGraph [ deployment ] framework = "langgraph" entrypoint = "src.my_agent.graph:graph" python = "3.11"
Basic LangGraph.js [ deployment ] framework = "langgraph-js" entrypoint = "./src/graph.ts:graph"
Web Scraping Crew [ deployment ] framework = "crewai" entrypoint = "src.scraper.crew:ScraperCrew" profile = "browser" python = "3.11" [ runtime ] timeout = 600 memory = 1024
Document Processing [ deployment ] framework = "crewai" entrypoint = "src.processor.crew:ProcessorCrew" python = "3.11" [ build . install ] packages = [ "poppler-utils" , "tesseract-ocr" ] [ runtime ] timeout = 900 memory = 2048
Slack Chatbot [ deployment ] framework = "crewai" entrypoint = "src.support_bot.flows.chat_flow:ChatFlow" python = "3.11" [ apis ] enabled = [ "thread" ] [ chat ] input_key = "query" output_key = "messages"
Multi-Agent Monorepo (mixed frameworks) [ build ] exclude = [ "tests" , "notebooks" ] [ deployments . research-agent ] framework = "crewai" entrypoint = "agents.research.crew:ResearchCrew" profile = "browser" python = "3.11" [ deployments . writer-agent ] framework = "langgraph" entrypoint = "agents.writer.graph:graph" python = "3.11" [ deployments . frontend-agent ] framework = "langgraph-js" entrypoint = "./agents/frontend/graph.ts:graph"
Deploy individual agents:
crewship deploy --name research-agent crewship deploy --name writer-agent
Deploy Deploy your configured crew
Slack Integration Connect your crew to Slack
Environment Variables Configure secrets
Threads Multi-turn conversations
