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John's Essentials

by com.johnsessentials

convert_geo

GPS & Map Converter — Convert between GPX, KML, KMZ and GeoJSON — the GPS-track and mapping formats used by Garmin, Strava, Google Earth and every GIS tool. Track segments, per-point timestamps, elevations and polygon holes all survive the trip. Anything that cannot survive (a polygon becoming a GPX track, an unlocated feature) is reported in the X-Conversion-Notes header rather than dropped quietly; pass strict=true to refuse instead. [category: convert]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesMust differ from the detected source — gpx→gpx is a 400; format-version upgrades happen implicitly on read.
fileYesA .gpx, .kml, .kmz or .geojson file.
fromNoOptional. Detected from content; declare it only when the upload has no meaningful filename.
strictNoWhen true, refuse the conversion instead of returning a result that loses information.

Schema Changelog

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

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The description goes well beyond the sparse annotations by disclosing that lossy conversions are reported in X-Conversion-Notes rather than silently dropped, and that strict=true changes behavior to refusal. It also lists which data features survive, adding meaningful operational insight.

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 dense but efficiently organized, leading with purpose, then preservation guarantees, then error-handling behavior. Minor stylistic flourishes like 'all survive the trip' do not waste space and reinforce user expectations.

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 four-parameter converter with no output schema, the description covers supported formats, preservation details, and lossy-conversion handling. It does not explicitly describe the response envelope, but the operation and schema make the returned converted file predictable.

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%, with each parameter already described including the gpx→gpx 400 rule and strict behavior. The description's mention of strict=true merely echoes the schema, so it adds little over the structured input.

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 ('Convert') plus the exact resource set (GPX, KML, KMZ, GeoJSON), and names the GPS/mapping ecosystem. This clearly distinguishes it from sibling convert_* tools like convert_document or convert_video without needing to open schemas.

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 gives clear context by defining the supported geospatial formats and typical use cases (Garmin, Strava, Google Earth, GIS). It does not explicitly name alternative tools or when not to use this one, but the domain specificity makes selection straightforward.

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

B3.2/5.0
Disambiguation2/5

Multiple tool pairs are near-identical: octopus_mkdir/octopus_make_folder and octopus_move/octopus_move_file are literal duplicates, analyze_hash/generate_hash both compute hashes, convert_word_to_pdf overlaps convert_document, and photo_compress/photo_compress_to_size plus pdf_thumbnails/pdf_to_images have fuzzy boundaries. The descriptions are detailed and cross-reference each other helpfully, but at 144 tools an agent will regularly misselect.

Naming Consistency3/5

The dominant {category}_{verb}_{object} snake_case pattern (pdf_*, photo_*, convert_*, analyze_*, media_*) is largely consistent and predictable. However, outliers like chatwithyourpdf and describe_image break the category-prefix convention, and the octopus namespace mixes bare verbs (read, write, mkdir) with verb_noun forms (make_folder, move_file, search_meta) inconsistently.

Tool Count2/5

144 tools is an extreme count for any MCP server. The broad scope (PDF, photo, video, audio, conversion, analysis, generation, file storage, web, e-sign) justifies some volume, but the count is inflated by batch and inspect variants (pdf_to_excel + batch + inspect), duplicate tools, and overlapping converters. An agent faces an overwhelming selection surface.

Completeness4/5

Per-domain coverage is remarkably deep: PDF spans merge/split/compress/protect/unlock/metadata/OCR/watermark and bidirectional conversion; photo covers editing, format conversion, face handling, OCR, and collage; file storage has full CRUD plus search. Minor gaps exist (no audio transcription, no video metadata editing, no deletion of PDF pages is actually covered via pdf_delete_pages) but the surface has no dead ends for its declared domains.

Resources