Skip to main content
Glama
HarshShinde0

GeoCroissant MCP Server

by HarshShinde0

extract_distribution_urls

Extract concrete dataset download URLs from Croissant/GeoCroissant metadata, along with formats, sizes, and checksums, so ingestion code can fetch data files without manual JSON parsing.

Instructions

Extracts downloadable URLs from a Croissant document's distribution.

    Collects the `contentUrl` of every FileObject together with its encoding
    formats, sizes and checksums, plus FileSet include patterns and archive
    containers. These are the direct access points for the dataset bytes.

    Usage: Use this tool to obtain concrete download links (e.g. GeoTIFF /
    COG / ZIP assets) for ingestion code without parsing the JSON manually.

    Returns:
    --------
    DistributionUrls containing:
        - urls: One entry per distribution item (name, type, contentUrl,
          encodingFormat, md5/sha256, includes/containedIn when present).
        - count: Number of distribution items with at least one URL.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jsonld_urlNoURL of a Croissant/GeoCroissant JSON-LD document.
jsonld_pathNoPath to a local Croissant/GeoCroissant file.
jsonld_contentNoRaw JSON string of a Croissant document.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesOne entry per FileObject/FileSet: name, contentUrl(s), encodingFormat and hashes when declared.
countYesNumber of distribution entries with URLs.
Behavior4/5

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

No annotations are provided, so the description carries full responsibility. It thoroughly explains what is extracted, the output structure, and the count semantics. Potential error conditions or network behavior are not mentioned, but for a pure extraction tool this is adequate.

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?

The description is front-loaded with a one-sentence purpose, followed by a compact extraction details list, a usage note, and a structured return section. There is slight redundancy between 'downloadable URLs' and 'contentUrl', but every block adds useful context without excessive length.

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 three optional parameters and a defined output schema, the description provides all necessary context: the purpose of starting extraction, a compressed return value structure, and number of items. An agent can correctly invoke the tool with any of the three compatible input sources and interpret the output.

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?

All three input parameters (jsonld_url, jsonld_path, jsonld_content) already have descriptions in the schema, so schema coverage is 100%. The description does not add parameter-specific guidance; however, since the schema handles that, the baseline 3 is appropriate.

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 uses a specific verb-object pair ('Extracts downloadable URLs from a Croissant document's distribution') and enumerates the exact data captured: contentUrl per FileObject, encoding formats, sizes, checksums, FileSet includes patterns. This fully differentiates it from sibling tools like inspect_geocroissant or get_structure_graph, which handle different aspects.

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 'Usage' sentence clearly states when to invoke this tool: to obtain concrete download links (e.g., GeoTIFF/COG/ZIP) for ingestion code without parsing the JSON manually. It does not explicitly list exclusions or alternative tools, but the primary use case is unambiguous.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/HarshShinde0/geocr_mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server