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ball2jh

findagrave-com-mcp

by ball2jh

Download a Find a Grave photo

findagrave_download
Idempotent

Fetch a Find a Grave memorial or cemetery photo by photo ID or URL. Return it inline scaled to maxSide, or write the original file to a local path.

Instructions

Fetch a memorial or cemetery photo (a gravestone, portrait, obituary clipping, …). Action photo: needs photoId (from findagrave_memorial get/photos) or url (an images.findagrave.com URL). Without outPath the image is returned inline for reading, scaled so its longer side is at most maxSide (default 1600 px). With outPath the original file is written to disk unscaled (unless maxSide is given) and only metadata is returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoPhoto URL on images.findagrave.com, instead of photoId
actionYesphoto
maxSideNoScale so the longer side is at most this many pixels (inline default 1600; with outPath the default is the original size)
outPathNoAbsolute local path to write the image to (overwritten if it exists)
photoIdNoPhoto id from findagrave_memorial get or photos

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

The description adds significant behavioral detail beyond annotations: inline responses are scaled to maxSide default 1600 px, while outPath writes the original file unscaled and returns only metadata. This explains the side-effect mode meaningfully despite idempotentHint=true.

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 dense sentences convey scope, input requirements, scaling behavior, and return behavior with no filler. The most important distinction (inline vs file output) is front-loaded and clearly structured.

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 single-action photo fetch tool, the description covers input alternatives, source guidance, output modes, scaling defaults, and return type. There is no output schema, so the description rightly explains what the caller gets in each mode.

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?

The schema already documents every parameter thoroughly (100% coverage), so baseline is 3. The description adds value by stating that photoId and url are alternatives, clarifying the inline-vs-disk behavior tied to outPath, and noting that only metadata is returned with outPath.

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 opens with a specific verb and resource: "Fetch a memorial or cemetery photo," with concrete examples. This clearly distinguishes the tool from its metadata-focused siblings like findagrave_memorial and findagrave_place.

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 clearly explains the two input routes (photoId vs url) and the two output modes (inline reading vs writing to outPath). It references findagrave_memorial get/photos as the source for photoId, but does not explicitly state when to prefer this tool over alternatives or include exclusions.

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