Get Catalog
get_catalogFree discovery. Returns the list of live agent-ready data packs available on DaedalMap.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_catalogFree discovery. Returns the list of live agent-ready data packs available on DaedalMap.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true. The description adds context about the data (live, agent-ready) but does not disclose any additional behavioral traits like caching, rate limits, or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences (13 words) with no wasted text. It is front-loaded with 'Free discovery' and immediately defines the output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description is mostly complete. It could mention if the list is ordered or if there are any limitations, but overall it suffices.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is 100%. According to guidelines, baseline is 4. No additional parameter information needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a list of live agent-ready data packs available on DaedalMap, using a specific verb and resource. It distinguishes from siblings like get_pack, which likely retrieves a single pack.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Free discovery' implies when to use this tool (for initial exploration), but it does not explicitly compare with alternatives or state 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.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: point resolution, reference conversion, hierarchy traversal, geometry retrieval, export creation, job estimation, catalog discovery, and relationship comparison are all separated. The descriptions explicitly state what each tool does and what it does not do, preventing misselection. Even closely related tools like get_geometry, get_geometry_export, and estimate_geometry_package are differentiated by their roles (single-shape retrieval vs. export artifact vs. dry-run estimate).
All 20 tool names follow a consistent verb_noun snake_case pattern (e.g., get_geometry, create_conversion_job, resolve_point, list_reference_systems). The verbs are action-oriented (get, create, estimate, resolve, compare, list, read) and each noun clearly indicates the subject. While a few like 'loc_id_info' and 'how_geometry_works' deviate slightly from the strict verb_noun structure, they still fit the overall style and are easy to predict.
The 20 tools are slightly above the typical 3-15 range but still well-scoped for a comprehensive geocoding and geography service. The extra tools reflect the breadth of operations offered (discovery, conversion, estimation, export, resolution, relationship analysis), each earning its place. The count feels reasonable given the domain, though it approaches the upper boundary of what an agent might easily navigate.
The tool surface covers the full lifecycle of geocoding workflows: discovery (get_catalog, get_pack, read_geometry_catalog), point resolution (resolve_point), reference resolution (resolve_reference), identifier identification (identify_reference_system), hierarchy traversal (resolve_loc_id_scope, loc_id_info), geometry retrieval (get_geometry), relationship analysis (compare_geographies), conversion (convert_reference, create_conversion_job), export (create_geometry_export), and estimation (estimate_geometry_package, estimate_conversion_job). The inclusion of help tools (get_tool_help, how_geometry_works) and job status retrieval ensures no dead ends. The absence of destructive or update operations is consistent with a read-only geospatial data service, so the surface is appropriate.