Extend MCP

Get an extractor (or one of its versions)

get_extractor

Read-onlyIdempotent

Get an extractor with its draft config, or one specific version's config via version (extract group). Use list_extractors to discover IDs. Follow any llmContext guidance included in results.

Input Schema

TableJSON Schema

Name	Required	Description
`id`	Yes	Extractor ID (ex_...).
`version`	No	"draft", "latest" (latest published), "MAJOR.MINOR" (e.g. "1.2"), or an exv_... version ID.
`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
`config`	No
`version`	No
`draftVersion`	No

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already establish that this is read-only, idempotent, and non-destructive. The description adds useful behavioral context: results may include llmContext guidance to follow, and the tool can return either draft or version-specific configs. It does not cover permission or not-found behavior, but the safety profile is already handled by annotations.

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

Conciseness4/5

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

The description is three short sentences with the core behavior front-loaded, followed by discovery and result-handling guidance. The parenthetical '(extract group)' is slightly awkward and adds little clarity, but overall the text is compact and free of fluff.

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?

For a read-only getter with full parameter schema and an output schema, the description covers the main access patterns: draft configs, versioned configs, ID discovery via list_extractors, and following llmContext guidance. It does not mention list_extractor_versions for discovering version IDs, but the version parameter schema already documents the accepted version identifiers, so this is a minor gap.

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

Parameters3/5

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 four parameters, including the version forms and environment enum. The description adds a little meaning by mapping 'draft' to the draft config and suggesting list_extractors for IDs, but it does not substantially expand on the parameters.

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 uses a specific verb-resource pair and clearly distinguishes the two main cases: fetching an extractor's draft config or fetching a specific version's config. It also points to list_extractors for ID discovery, which helps differentiate this getter from the listing sibling.

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?

It gives concrete routing guidance: use list_extractors to discover IDs, and use this tool to get draft or versioned extractor configs. It does not explicitly state when not to use the tool, such as using list_extractor_versions to enumerate available versions, so it falls just short of full guidance.

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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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

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