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DaedalMap Wildfire Events

Server Details

Wildfire events and aggregates across global, U.S., and Canada sources. Paid via x402 USDC.

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Status
Healthy
Last Tested
Transport
Streamable HTTP
URL
Repository
xyver/daedal-map
GitHub Stars
2
Server Listing
daedal-map

Available Tools

7 tools
get_catalogGet CatalogA
Read-only
Inspect

Free discovery. Returns the list of live agent-ready data packs available on DaedalMap.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.3/5.0
Behavior3/5

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

The readOnlyHint annotation already covers safety, and the description adds minimal context (e.g., 'live' and 'agent-ready'). It does not detail output structure, pagination, or potential side effects, which is a gap given the absence of an output schema. However, for a zero-parameter read-only tool, the description is not misleading.

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 two sentences: 'Free discovery.' and 'Returns the list of live agent-ready data packs available on DaedalMap.' It is front-loaded with a clear phrase, every word earns its place, and it avoids redundancy.

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 the tool's simplicity (no parameters, no output schema, read-only annotation), the description adequately covers the essential return value and context. It tells the agent exactly what to expect: a list of live, agent-ready data packs. No further details are necessary for this kind of discovery 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 zero parameters, so the baseline for parameter semantics is 4. No parameter details are needed, and the description correctly focuses on the return value. There is nothing to complain about here.

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 ('Returns') and resource ('list of live agent-ready data packs'). It distinguishes itself from sibling tools focused on disaster links and data queries, making its function obvious.

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 phrase 'Free discovery' suggests a low-cost way to explore available data packs, but it does not explicitly mention when to use this tool over alternatives like get_pack or query_dataset. It provides clear context without exclusions, fitting the 'clear context, no exclusions' baseline.

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

get_packGet PackA
Read-only
Inspect

Free discovery. Returns detailed metadata, coverage, freshness, preferred canonical tool guidance, and first-query examples for one pack. Call this before querying a new pack so you can see time shape, coverage limits, and the paste-ready first query.

ParametersJSON Schema
NameRequiredDescriptionDefault
pack_idYesPack identifier from get_catalog. Newly catalog-admitted packs require no MCP schema change.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, lowering the bar. The description adds genuine context beyond that: 'Free discovery' signals no cost, and it discloses what the agent will gain (time shape, coverage limits, paste-ready first query), which frames it as a safe prerequisite step. No contradiction with annotations.

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?

Two sentences with no waste. The scoping phrase 'Free discovery' is front-loaded, followed by the return payload, then the actionable prerequisite guidance. Every clause earns its place and the structure aids a quick scan.

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?

Although there is no output schema, the description compensates by enumerating the return contents (metadata, coverage, freshness, canonical tool guidance, first-query examples). For a single-parameter, read-only discovery tool this is complete — an agent knows exactly what it will receive and when to call it.

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 description coverage is 100% — pack_id is fully documented ('Pack identifier from get_catalog'). Per the rubric, this warrants a baseline 3. The description references 'one pack' consistent with the single parameter but adds no syntax or format detail beyond the schema, which is acceptable given full coverage.

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 states a specific verb and resource: 'Returns detailed metadata, coverage, freshness, preferred canonical tool guidance, and first-query examples for one pack.' It clearly distinguishes itself from siblings — get_catalog enumerates packs, query_dataset runs queries, while get_pack fetches metadata for a single pack, reinforced by 'preferred canonical tool guidance' which no sibling mentions.

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?

It gives explicit timing guidance: 'Call this before querying a new pack so you can see time shape, coverage limits, and the paste-ready first query.' This tells the agent when to invoke it in a workflow. It lacks an explicit exclusion naming a specific alternative, but the prerequisite framing is clear enough to route correctly.

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

get_tool_helpGet Tool HelpA
Read-only
Inspect

Free blind-caller guidance for one tool visible on this MCP facade. Returns when to use it, what it refuses, a working example, effective access limits, important outputs, provenance fields, recommended next calls, and the shared natural-language-to-strict-JSON interaction contract. Use tools/list to discover names, then call this before an unfamiliar tool.

ParametersJSON Schema
NameRequiredDescriptionDefault
tool_nameYesExact tool name from tools/list.

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the agent knows the tool is safe and non-mutating. The description adds value by disclosing what the tool returns: 'when to use it, what it refuses, a working example, effective access limits, important outputs, provenance fields, recommended next calls, and the shared natural-language-to-strict-JSON interaction contract.' This gives a detailed picture of the tool's output behavior without contradicting the annotations. It doesn't mention potential errors (e.g., unknown tool name), but that's a minor gap.

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 three sentences and front-loaded with purpose. The second sentence lists important output categories – a bit long but every item adds value. The final sentence gives a clear call-to-action. No fluff, but the list is dense. It earns its length and does not waste the reader's attention.

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 no output schema, the description must explain return values, and it does by enumerating the content types. It also covers the discovery workflow and when to use the tool. It doesn't describe error behavior for invalid tool names, but given the low parameter count and simple purpose, the description is sufficiently complete for an agent to invoke the tool effectively.

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 description coverage is 100% – the only parameter 'tool_name' is described as 'Exact tool name from tools/list.' The description reinforces this by saying 'Use tools/list to discover names,' providing a helpful hint about the parameter's source. However, it adds no format, validation, or default information beyond what the schema already provides. The baseline of 3 applies because the schema fully documents the parameter.

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 function: 'Free blind-caller guidance for one tool visible on this MCP facade.' It uses a specific verb ('returns') and identifies the resource ('one tool'). It also lists concrete deliverables, distinguishing it from sibling tools that retrieve data (e.g., get_catalog, query_dataset). The purpose is unambiguous and front-loaded.

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 provides explicit workflow: 'Use tools/list to discover names, then call this before an unfamiliar tool.' This tells the agent when to use the tool and gives a clear prerequisite step. It does not explicitly state when not to use it, but the guidance is strong enough for an AI agent to select it appropriately. The mention of 'before an unfamiliar tool' signals a clear use case.

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

query_datasetQuery DatasetA
Read-only
Inspect

Generic structured query for direct source_id or pack_id access using the same contract as POST /api/v1/query/dataset. Free packs: currency, distributed_manufacturing, floods, nri, owid, un_sdg, un_wpp, volcanoes, world_bank_wdi. Paid packs: earthquakes, hurricanes, tornadoes, tsunamis, wildfires, world_factbook, worldpop (x402 Base USDC).

ParametersJSON Schema
NameRequiredDescriptionDefault
sortNoOptional sort instructions for row-returning queries.
limitNoMaximum number of rows to return for the requested source or pack.
outputNoOptional output controls such as response format hints.
filtersNoStructured filters including time, region_ids, and compare clauses.
metricsNoMetric ids to return. Use event_count for aggregate counts when supported.
pack_idNoPack identifier from get_catalog. Newly catalog-admitted packs require no MCP schema change.
source_idNoConcrete source id such as 'earthquakes_events', 'volcanoes_events', 'hurricanes_events', or 'un_sdg/01'.
request_idNoOptional caller-supplied request id for tracing and idempotency.

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds useful behavioral context beyond that: the exact API contract, the distinction between free and paid packs, and the x402 Base USDC payment requirement. It does not describe the response shape, but safety-related behavior is well covered.

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?

Two sentences deliver the essential purpose, contract, and pack availability with no filler. The primary access mode is front-loaded, and the pack list is compact and directly useful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 8 parameters, no required fields in the schema, and no output schema, the description should clarify that a source_id or pack_id must typically be provided. It relies on the external API contract reference and leaves some invocation details implicit. Still, the schema descriptions and pack list cover much of what an agent needs.

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 description coverage is 100%, so the baseline is 3. The description adds the pack list and payment context but does not add parameter-level semantics beyond what the input schema already provides. It only reinforces the source_id/pack_id access model.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies a specific verb ('query') and resource ('dataset') and explains that it provides direct access via source_id or pack_id. It names the backing API contract. However, it does not explicitly contrast itself with siblings like get_pack or get_catalog, so it stops short of full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool: when you have a direct source_id or pack_id and need structured data. It also lists free vs. paid pack availability, which helps selection. But it does not explicitly say when not to use it or point to an alternative sibling tool for catalog listing or pack metadata.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 2 tool updates
    • Changedget_pack1 field changed
      • changedInput schema / properties / pack_id / description
        Previous value: -"Pack identifier such as 'currency', 'earthquakes', 'floods', 'hurricanes', 'tornadoes', 'tsunamis', 'un_sdg', 'volcanoes', 'world_factbook', or 'worldpop'."New value: +"Pack identifier from get_catalog. Newly catalog-admitted packs require no MCP schema change."
    • Changedquery_dataset1 field changed
      • changedInput schema / properties / pack_id / description
        Previous value: -"Pack identifier such as 'currency', 'earthquakes', 'floods', 'hurricanes', 'tornadoes', 'tsunamis', 'un_sdg', 'volcanoes', 'world_factbook', or 'worldpop'."New value: +"Pack identifier from get_catalog. Newly catalog-admitted packs require no MCP schema change."
  2. 1 tool update
    • Addedget_tool_help
  3. 3 tool updates
    • Addedget_disaster_link_chain
    • Addedget_disaster_links_for_event
    • Addedsearch_disaster_links
  4. 3 tool updates
    • First observedget_catalog
    • First observedget_pack
    • First observedquery_dataset

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TDQS

A4/5.0
Disambiguation4/5

Tools are mostly distinct: discovery (get_catalog, get_pack), query (query_dataset), and linked-disaster helpers (get_disaster_link_chain, get_disaster_links_for_event, search_disaster_links) are clearly separated. However, get_disaster_link_chain and get_disaster_links_for_event both expand an event id into related events/links, which could cause confusion even though descriptions explain the difference.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case: get_catalog, get_pack, get_disaster_link_chain, query_dataset, search_disaster_links. The naming is uniform and predictable.

Tool Count4/5

Seven tools is within the typical well-scoped range. The mix of discovery, query, and helper tools covers the server's facade purpose, though none are strictly wildfire-specific. The count feels reasonable, not excessive or sparse.

Completeness4/5

The server provides discovery (catalog, pack metadata), an arbitrary query interface, and linked-disaster helpers, covering the main access patterns. Minor gaps exist, such as no direct 'list events' tool separate from query, but query_dataset likely handles retrieval. Overall, the surface is coherent for a data-access server.