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sheetsdata-mcp

by io.github.octoco-ltd

get_part_details

Read-only

Get full details for a specific electronic component by manufacturer part number (MPN) or LCSC number. Returns specs, pricing, and stock from all configured providers, plus the cached datasheet summary if available. Includes datasheet_status and available_sections when ready. Set prefetch_datasheet=true to trigger background extraction — no extra charge. Use after search_parts to drill into a specific result.

The part_number must be a specific manufacturer part number (e.g. 'TPS54302DDCR', 'STM32F446RCT6') or LCSC number (e.g. 'C2837938'). Do NOT pass bare component values ('100nF', '10K'), descriptions ('buck converter'), or reference designators ('R1', 'U3').

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
providerNoWhich provider to query: 'all' (default), 'jlcpcb', 'mouser', or 'digikey'all
part_numberYesSpecific manufacturer part number (MPN) or LCSC number (e.g. 'C2837938'). Not a value or description.
prefetch_datasheetNoTrigger background datasheet extraction (no extra charge). Default false.

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already state readOnlyHint=true and destructiveHint=false, and the description goes far beyond by explaining prefetch_datasheet behavior, no extra charge, and a complete datasheet status lifecycle with recommended polling intervals and retry actions. This adds significant context about asynchronous behavior and error handling without contradicting 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.

Conciseness4/5

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

The description is long but well-structured: a clear opening summary, usage guidance, and a detailed datasheet status section formatted as a list. Every status value earns its place because it informs actionable next steps, though a few redundant phrases like 'extraction running or scheduled' could have been trimmed.

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?

Given the tool's complexity (multiple statuses, background extraction, provider options) and no output schema, the description is comprehensive. It covers what the tool does, what it returns, how to handle each datasheet state, and pointers to related tools for additional actions, making it self-sufficient for an agent.

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

Parameters5/5

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

Schema coverage is 100% with each parameter having a description, but the narrative adds extra meaning: real MPN examples, explicit negative examples for part_number, and semantic details about prefetch_datasheet as a background trigger with no charge. This far exceeds the schema's basic field descriptions.

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 it fetches full details for a component by MPN/LCSC number and lists return contents (specs, pricing, stock, datasheet summary). It uses a specific verb ('Get full details') and resource ('specific electronic component'), differentiating it from search_parts and other siblings.

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?

Explicitly instructs to use after search_parts to drill into a result, and provides concrete restritions on what part_number should NOT contain (bare values, descriptions, reference designators). The extensive datasheet status section also recommends when to call check_extraction_status, read_datasheet, prefetch_datasheets, or upload tools, giving clear alternative routes.

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