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sheetsdata-mcp

by io.github.octoco-ltd

check_extraction_status

Read-onlyIdempotent

Check the extraction status of one or more parts. Free. Each entry includes the current extraction step, elapsed seconds, and document ID.

Use after prefetch_datasheets or after read_datasheet triggers a new extraction.

Recommended polling cadence: every 5-10 seconds. Extraction typically takes 30s-2min for new parts, so polling faster than every 5s wastes calls. Stop polling once status is 'ready', 'failed', 'no_source', or 'unsupported'.

DATASHEET STATUS VALUES:

  • 'ready' — extracted and indexed; call read_datasheet, search_datasheets, or analyze_image.

  • 'extracting' / 'in_progress' / 'queued' / 'pending' — extraction running or scheduled. Poll check_extraction_status every 5-10s until 'ready' or 'failed'. Typical time: 30s-2min.

  • 'not_extracted' — known part but datasheet hasn't been fetched yet. Trigger it via prefetch_datasheets (cheapest) or by calling read_datasheet (auto-triggers on first read).

  • 'no_source' — we couldn't find a public datasheet URL for this MPN. First, retry prefetch_datasheets in 10-30s (the URL resolver re-runs and often finds a source on the second pass). If still 'no_source', the agent can upload the PDF manually via request_datasheet_upload + confirm_datasheet_upload (see those tools). Org-uploaded datasheets are private to the org.

  • 'unsupported' — PDF exists but can't be extracted (scanned image-only, encrypted, or corrupted). Upload a clean text-based PDF via request_datasheet_upload to override.

  • 'failed' / 'error' — extraction errored. The response includes the error reason. Retry via prefetch_datasheets or escalate to support.

  • 'rejected' — input wasn't a real MPN (bare value like '100nF', description, or reference designator). Fix the input and re-call.

  • 'deduplicated' — another part in the family already has this datasheet; same content is returned under the primary MPN.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
part_numbersYes1-20 MPNs to check. Must be specific manufacturer part numbers, not values or descriptions.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / part_numbers / description
      Previous value: -"List of MPNs to check (max 20)"New value: +"1-20 MPNs to check. Must be specific manufacturer part numbers, not values or descriptions."
  2. First observed

TDQS

A4.9/5.0
Behavior5/5

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

The description adds rich behavioral context beyond annotations: it is free, includes elapsed seconds and document ID, explains the meaning of every status value, notes that no_source may resolve on retry, and discloses that org-uploaded datasheets are private. This goes well beyond the readOnly/idempotent hints, with no contradictions.

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 front-loaded with the purpose and usage, then organized into a clear status-value list. Every sentence provides actionable information; the length is justified by the number of distinct statuses and the need to give follow-up actions for each.

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?

With no output schema, the description fully compensates by enumerating all possible statuses, typical durations, recommended polling, and next-step actions. It also notes response contents (step, elapsed seconds, document ID, error reason), making it complete for practical use.

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 parameter description already explains MPN requirements. The tool's description adds value by explaining the 'rejected' status as a consequence of invalid inputs, and clarifies that each entry corresponds to a part number, reinforcing the semantics without redundancy.

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 clearly states the tool checks extraction status of one or more parts, with a specific verb and resource. It distinguishes itself from siblings like prefetch_datasheets and read_datasheet by focusing on status polling and listing terminal states.

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

Usage Guidelines5/5

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

Explicit guidance is given on when to use: after prefetch_datasheets or when read_datasheet triggers extraction. It provides polling cadence, stopping conditions, and specific alternative tools for each non-ready status (e.g., prefetch_datasheets for not_extracted, request/confirm upload for no_source/unsupported).

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

A4.8/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: search_parts finds parts, search_datasheets searches extracted content, read_datasheet reads sections, analyze_image extracts visual data, compare_parts batches comparisons, find_alternative finds substitutes, check_design_fit validates specs, prefetch/check/manage extraction status, and request/confirm handle uploads. The descriptions cross-reference each other to further eliminate ambiguity.

Naming Consistency5/5

All 12 tools follow the verb_noun snake_case pattern consistently (analyze_image, check_design_fit, compare_parts, prefetch_datasheets, request_datasheet_upload, etc.). No mixing of camelCase, verb styles, or vague generic names.

Tool Count5/5

12 tools is ideal for a datasheet-centric server, covering the full workflow from part discovery and datasheet extraction to analysis, validation, comparison, and upload. The count is neither bloated nor thin, and every tool earns its place.

Completeness5/5

The tool surface is comprehensive for the domain: part search, spec-based semantic search, detailed part data, datasheet reading (section/search), image analysis, design-fit checking, part comparison, alternative finding, extraction lifecycle management, and manual datasheet upload (request+confirm). No obvious dead ends or critical missing operations.

Resources