Extend MCP

Deploy a workflow version

deploy_workflow_version

Deploy the workflow's current draft as a new immutable version (workflows group). Unlike extractor/classifier/splitter publishing there is NO releaseType — workflow versions are integer deploy numbers ("1", "2", ...) with an optional display name referenced at run time. Pass steps to deploy that graph instead of the draft. Deployed versions never change — keep iterating on the draft.

Input Schema

TableJSON Schema

Name	Required	Description
`id`	Yes	Workflow ID (workflow_...).
`name`	No	Display name for this deployed version (max 255 chars).
`steps`	No	Deploy these steps instead of the current draft. Step graph (max 100 steps), TRIGGER → PARSE first. Every step needs { type, name }; "name" is REQUIRED and is what other steps route to. Route via next, an ARRAY of objects: linear steps (TRIGGER/PARSE/EXTRACT) use next: [{ step: "<target name>" }]; CLASSIFY/SPLIT branch with next: [{ step, classificationId }] (classificationId = a classification id from the config, not its type). TRIGGER routes to exactly one PARSE. Types: TRIGGER, PARSE, EXTRACT, CLASSIFY, SPLIT, MERGE_EXTRACT, CONDITIONAL, CONDITIONAL_EXTRACT, EXTERNAL_DATA_VALIDATION, WEBHOOK_RESPONSE, RULE_VALIDATION, VALIDATION, ROUTER, HUMAN_REVIEW, COLLECT, FILE_CONVERSION. EXTRACT/CLASSIFY/SPLIT need a config with exactly one of a saved ref or inline config (EXTRACT: config.extractor {id,version} or config.extractorConfig with REQUIRED schema; CLASSIFY: config.classifier {id,version} or config.classifierConfig); next is only allowed once config is set. Classifier/splitter refs can't be "latest" — use semver or "draft". The rules here are a summary — before authoring a step graph by hand, call get_documentation with https://docs.extend.ai/workflows/configuring-workflows.md and follow it.
`environment`	Yes	"TEST" = the Test (development) environment, "PRODUCTION" = live. Must match a granted target from get_me (an API key pins one environment).
`workspaceId`	Yes	Target workspace (ws_...). Must be a granted workspace — get_me lists the accepted values.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes
`name`	No
`steps`	No
`version`	Yes
`createdAt`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 3, 2026

TDQS

A4.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate this is a mutating operation but not destructive, and the description adds meaningful behavioral context: deployed versions are immutable, integer deploy numbers, and iteration continues on the draft. This goes beyond the annotations by clarifying the versioning model and permanence of deployments.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core purpose before moving to distinctions and usage nuance. Every sentence earns its place, including the caution that deployed versions never change and iteration should continue on the draft.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The schema carries the heavy detail for the step graph and environment constraints, while the description fills in the workflow-specific versioning model and immutability. With annotations and an output schema present, the description is largely sufficient, though it could briefly mention relevant permissions or side effects given this is a mutating operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all parameters extensively. The description adds useful param-level nuance, such as names being referenced at runtime and the optional 'steps' override that deploys a graph instead of the draft. This supplements the schema rather than merely repeating it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description states a specific operation: deploy the workflow's current draft as a new immutable version in the workflows group. It clearly distinguishes itself from extractor/classifier/splitter publishing by noting the absence of releaseType and the integer deploy numbering. An agent can immediately understand what this tool uniquely does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool, contrasting it with publishing in other tool groups and explaining workflow-specific behavior. It does not give an explicit 'use this instead of X when Y' conditional, but the distinction from sibling publish tools is strong and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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