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bundle_migrate_convert

PAID (40 credits) — one-call file migration: convert a raw file to GeoJSON, then optionally reproject and simplify, then round coordinates. Replaces 2-4 separate free tool calls (convert + reproject + simplify + round) an agent would otherwise chain by hand — see estimate_cost's "replaces" field. Requires Authorization: Bearer and sufficient credits balance.

input_format: "shapefile" (data = base64-encoded .zip), "kml", "gpx", or
"csv" (data = raw text for the latter three).
to_epsg: 0 skips reprojection (keeps the converter's native WGS84 output).
simplify_tolerance: 0 skips simplification (Douglas-Peucker, degrees).
round_decimals: coordinate rounding, always applied (default 6).

Returns JSON: {ok, feature_count, geojson, reprojection_notice}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
to_epsgNo
input_formatYes
round_decimalsNo
simplify_toleranceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries full behavioral burden. It discloses the credit cost, auth requirement, input format specifics (shapefile as base64 .zip vs raw text), parameter edge cases (0 skips reprojection/simplification), and return format. This goes well beyond the empty schema descriptions, though it omits failure modes and rate limits.

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 longer than a two-liner but every sentence earns its place: purpose, benefit, auth, parameter breakdown, and return schema. It is front-loaded with the core purpose and uses a clear paragraph-per-aspect structure. Slightly verbose but not wasteful.

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 5-parameter tool with an output schema, the description is quite complete. It explains all parameters, return fields, and auth/credit constraints. It does not cover error cases or null handling, but those are less critical for a conversion tool. Overall it provides sufficient context for an agent to invoke it correctly.

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 description coverage is 0%, but the description compensates fully. It explains each parameter: input_format values and data encoding, to_epsg=0 meaning, simplify_tolerance=0 plus algorithm, round_decimals default, and how data relates to format. Every parameter is given meaningful usage context beyond the bare 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?

The description opens with 'one-call file migration: convert a raw file to GeoJSON, then optionally reproject and simplify, then round coordinates.' This is a specific verb+resource statement that clearly distinguishes the tool from individual conversion siblings like csv_to_geojson or reproject_geojson by emphasizing its bundling of multiple steps.

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 explicitly notes it 'Replaces 2-4 separate free tool calls... an agent would otherwise chain by hand' and references estimate_cost's 'replaces' field, giving clear when-to-use context. It also mentions prerequisites (Authorization header and credits), but does not explicitly state when to prefer individual tools, so it stops short of a 5.

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

B3.3/5.0
Disambiguation2/5

Many assess_* composite tools (datacenter, ev_charging, renewable, telecom, due_diligence) share the same building blocks of grid proximity, land cover, and terrain, making their boundaries fuzzy. assess_property_hazard_x402 also duplicates assess_property_hazard with only a payment-method difference, and bundle_* tools intentionally overlap with the free primitives they replace.

Naming Consistency3/5

There is a mix of verb_noun tools (query_features, geocode_address), noun-first geometry tools (centroids_geojson, envelope_geojson), and inconsistent _geojson suffix usage (buffer_geojson, fix_geometry, geometry_stats). The assess_* and bundle_* prefixes offer some grouping, but no single naming pattern is followed across the set.

Tool Count1/5

With 85 tools, the surface is extreme for an MCP server and far exceeds the typical well-scoped 3-15 range. Many tools are convenience bundles or variants that could be consolidated, making the count a significant usability burden.

Completeness4/5

The toolkit covers a broad range of GIS tasks: format conversions, GeoJSON analysis, FeatureServer query/inspection, geocoding, site assessment, and sharing. Minor gaps exist (e.g., no Excel-to-GeoJSON, no FeatureServer update/delete), but most missing functionality can be worked around by chaining existing tools.