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. Follow any llmContext guidance included in results.

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

TDQS

A4.4/5.0

Behavior4/5

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

Annotations establish this is a mutating, non-idempotent operation (readOnlyHint=false, idempotentHint=false). The description adds meaningful behavioral context beyond that: versions are immutable, use integer deploy numbers, have no releaseType, and an optional display name referenced at run time. No contradiction with annotations.

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?

Four sentences with zero waste, front-loaded with the core purpose and immediately followed by the key sibling distinction. Every sentence earns its place, including the irreversibility note and the llmContext reminder.

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?

Given the very rich parameter schema, existing output schema, and annotations, the description covers the essential deployment semantics (immutability, numbering, draft vs. steps, runtime reference). The main gap is routing the agent toward run_workflow for executing the deployed version, but the complex step-graph rules are already delegated to get_documentation in the schema.

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% and the steps parameter description is exceptionally detailed, so the baseline is 3. The description adds value on top by explaining the steps/name semantics: 'Pass steps to deploy that graph instead of the draft' and 'optional display name referenced at run time', which clarify relationships not fully spelled out in the schema.

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?

The description states a specific verb and resource: 'Deploy the workflow's current draft as a new immutable version (workflows group)'. It explicitly distinguishes itself from the sibling publishing tools by stating 'Unlike extractor/classifier/splitter publishing there is NO releaseType', so an agent can tell it apart without opening schemas.

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 gives clear usage context: deploy makes an immutable run-time version, 'Deployed versions never change — keep iterating on the draft', and it contrasts the workflow deploy path with extractor/classifier/splitter publishing. It does not explicitly state when to use run_workflow instead of deploying, so the guidance stops short of a full when-to-use/when-not-to-use matrix.

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

All Extend MCP tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0

Disambiguation5/5

Each tool targets a distinct resource+action combination, and the descriptions actively disambiguate potential overlaps (e.g., extract_data vs parse_document, detect_form_fields vs edit_pdf, get_file vs get_file_upload). The consistent verb_noun prefix pattern makes the semantic boundary of every tool immediately recognizable.

Naming Consistency4/5

The dominant verb_noun pattern is highly consistent across all nine domains (list_*, get_*, create_*, update_*, delete_*, run_*, get_*_run, get_*_batch, publish_*_version). Minor deviations exist: deploy_workflow_version vs publish_*_version for the same freeze-a-draft concept, and get_form_detection_run doesn't mirror its detect_form_fields counterpart.

Tool Count2/5

86 tools is a very heavy agent-facing surface, well past the 25+ threshold. The count is inflated by the near-identical 13-tool lifecycle repeated across extract, classify, and split (each with list/get/create/update/publish/runs/batches/versions), and while each tool has a distinct purpose, the sheer volume makes selection harder.

Completeness4/5

Core lifecycles are thoroughly covered: create → update → publish → run (single and batch) → poll → cancel → delete-run → list runs/versions. Notable gaps include no delete tool for extractors, classifiers, splitters, workflows, or evaluation sets, and edit/form-detection runs have no list endpoint (documented workaround: keep run IDs). These are hygenic gaps that don't block primary workflows.

Resources

Need Help?