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OpenStreetMap Tagging Schema MCP Server

by gander-tools

Convert JSON to Flat Text

json_to_flat

Convert OpenStreetMap tags from JSON object to flat key=value text format, one tag per line, sorted alphabetically. Use to generate human-readable tag lists or export to OSM editors like JOSM and iD.

Instructions

Convert OpenStreetMap tags from JSON object format to flat text format (key=value per line). This is an OUTPUT CONVERTER for AI workflows - use it LAST when you need to present tags in a human-readable text format or export them for use in other tools. Produces clean, consistent key=value format with one tag per line, sorted alphabetically by key. Use this for generating human-readable tag lists, exporting to OSM editors, or sharing tag collections. The output format is compatible with JOSM, iD editor imports, and other OSM tools that accept flat text tag format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsYesTags as a JSON object (e.g., {"amenity": "restaurant", "name": "Test Cafe", "cuisine": "italian"}). All values must be strings. The output will be formatted as key=value pairs, one per line, sorted alphabetically.
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses the output format (key=value per line, sorted alphabetically) and that it's an output converter. No side effects mentioned, but none expected.

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 a single paragraph that front-loads the main purpose and adds details efficiently. No extraneous information, though it could be slightly more compact.

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?

With one parameter, no output schema, and no annotations, the description covers functionality, usage context, and output format adequately. Lacks an example but is otherwise complete.

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 description adds value by explaining the value constraint (strings) and the output formatting (sorted alphabetically), which goes beyond the schema's property description.

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 converts JSON to flat text format, specifying the resource (OpenStreetMap tags) and verb (convert). It distinguishes itself from siblings like flat_to_json by positioning as an output converter.

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?

Explicitly instructs to use it 'LAST' in AI workflows and lists concrete use cases (human-readable lists, export to editors). While it doesn't explicitly name alternatives for the reverse operation, the context is clear.

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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