Skip to main content
Glama
tharlestsa

OpenLandMap MCP Server

by tharlestsa

catalog_info

Retrieve metadata about the OpenLandMap STAC catalog, including its identifier, version, and available environmental datasets for geospatial analysis.

Instructions

Return metadata about the OpenLandMap STAC root catalog.

Returns the catalog identifier, description, STAC version, total number of collections, and conformance classes.

Example return: {"id": "openlandmap", "stac_version": "1.0.0", "total_collections": 104, ...}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The catalog_info tool handler implementation. It uses the STAC client to fetch catalog metadata and return it formatted as a CatalogInfo model.
    @mcp.tool()
    async def catalog_info() -> dict:
        """Return metadata about the OpenLandMap STAC root catalog.
    
        Returns the catalog identifier, description, STAC version, total number
        of collections, and conformance classes.
    
        Example return:
            {"id": "openlandmap", "stac_version": "1.0.0", "total_collections": 104, ...}
        """
        try:
            catalog = await client.get_catalog()
            index = await client.get_catalog_index()
        except STACClientError as exc:
            return {"error": f"Failed to fetch catalog: {exc}"}
    
        info = CatalogInfo(
            id=catalog.get("id", ""),
            description=catalog.get("description", ""),
            stac_version=catalog.get("stac_version", ""),
            total_collections=len(index),
            conformsTo=catalog.get("conformsTo", []),
        )
        return info.model_dump()
  • The Pydantic model defining the schema for the catalog_info tool's output.
    class CatalogInfo(BaseModel):
        """Root catalog metadata."""
    
        model_config = ConfigDict(frozen=True)
    
        id: str
        description: str
        stac_version: str
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns metadata (implying a read-only operation) and provides an example return format, which adds useful context. However, it does not mention behavioral aspects like error handling, rate limits, or authentication needs, leaving some gaps in transparency.

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 the core purpose, followed by specifics on what is returned and an example. Every sentence adds value—none are redundant or wasteful—making it efficiently structured and easy to parse.

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?

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is largely complete. It explains what the tool does and provides an example return. However, without an output schema, it could benefit from more detail on the full return structure or potential errors, but it adequately covers the basics for this simple tool.

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?

The tool has 0 parameters, and the input schema has 100% coverage (empty object). The description does not need to add parameter semantics, so it appropriately focuses on output. The baseline for 0 parameters is 4, as the description compensates by detailing the return value without unnecessary parameter information.

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's purpose with a specific verb ('Return') and resource ('metadata about the OpenLandMap STAC root catalog'), distinguishing it from siblings like list_collections or get_collection_schema. It explicitly mentions what metadata is returned (catalog identifier, description, STAC version, etc.), making the purpose unambiguous.

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 implies usage for retrieving high-level catalog metadata, but does not explicitly state when to use this tool versus alternatives like list_collections (which lists collections) or other sibling tools. It provides clear context for catalog-level information but lacks explicit exclusions or named alternatives.

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/tharlestsa/openlandmap_mcp'

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