Extend MCP

Get a parse batch

get_parse_batch

Read-onlyIdempotent

Get the aggregate status of a parse batch (parse group) submitted by run_parse_batch. wait: true polls until terminal. Statuses: PENDING, PROCESSING, PROCESSED, FAILED, CANCELLED. Follow any llmContext guidance included in results.

Input Schema

TableJSON Schema

Name	Required	Description
`wait`	No	Poll until the batch reaches a terminal status (within the wait budget).
`batchId`	Yes	The bpar_... ID from run_parse_batch.
`environment`	Yes	"TEST" = the Test (development) environment, "PRODUCTION" = live. Must match a granted target from get_me (an API key pins one environment).
`waitSeconds`	No	Max seconds to block waiting on the run (clamped to the server wait budget).
`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
`status`	Yes
`runCount`	No
`createdAt`	No
`updatedAt`	No
`llmContext`	No

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds beyond those by explaining wait polling, terminal status names, and the instruction to follow llmContext guidance within results. This is meaningful behavioral context not encoded in the 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?

Three short, dense sentences with no filler. The core purpose is front-loaded, and the status list plus llmContext note each earn their place as operationally useful details.

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

Completeness5/5

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

For a read-only, idempotent tool with a fully documented input schema and an output schema present, the description is complete. It covers the batch scope, polling behavior, statuses, and result-side guidance without over-explaining.

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 description coverage is 100%, so the baseline is 3. The description adds a small amount of semantic value by interpreting wait ('true polls until terminal') and naming the statuses, but it does not substantially expand on what each parameter means beyond 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?

States a specific verb ('Get'), a specific resource ('parse batch'), and the aggregate nature of the status, while naming the submitting sibling tool run_parse_batch. This clearly distinguishes it from get_parse_run and other batch getters.

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 explains when this applies (batches submitted by run_parse_batch) and how the wait parameter changes behavior. It does not explicitly exclude alternatives like get_parse_run, but the aggregate batch framing plus the wait/polling semantics gives solid usage context.

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.

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