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OpenStreetMap Tagging Schema MCP Server

by gander-tools

Convert JSON to Flat Text

json_to_flat

Converts OpenStreetMap tags from JSON object to flat key=value format, one per line, sorted alphabetically. Use for generating readable tag lists or exporting to OSM editors.

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?

Describes the output: one tag per line, sorted alphabetically, in key=value format. States all values must be strings. Without annotations, this provides adequate behavioral context, though edge cases (e.g., empty tags) are not addressed.

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 front-loaded with purpose and provides necessary context in a few sentences. Slight redundancy (e.g., 'human-readable' repeated) but overall efficient.

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 low complexity (1 parameter, no output schema), the description covers the transformation, output format, and compatibility, making it self-sufficient for an agent to invoke correctly.

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% so baseline is 3. The main description does not add new parameter details beyond the schema; it focuses on usage. The schema description already covers the parameter meaning.

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 converts JSON tags to flat text (key=value per line) and identifies itself as an output converter. It distinguishes from siblings like flat_to_json by specifying it's for final presentation/export.

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 says to use it 'LAST' in workflows for human-readable or export purposes, and lists compatible OSM tools. However, it does not explicitly mention alternatives like flat_to_json or when not to use it.

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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