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Glama

Server Details

Global flood events and extent 1985-present from the Dartmouth Flood Observatory and GFD.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL
Repository
xyver/daedal-map
GitHub Stars
3
Server Listing
daedal-map

Glama MCP Gateway

Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.

MCP client
Glama
MCP server

Full call logging

Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.

Tool access control

Enable or disable individual tools per connector, so you decide what your agents can and cannot do.

Managed credentials

Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.

Usage analytics

See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.

100% free. Your data is private.
Tool DescriptionsA

Average 4/5 across 4 of 4 tools scored.

Server CoherenceA
Disambiguation5/5

Each tool has a clearly distinct purpose: get_catalog lists available packs, get_pack provides metadata for one pack, query_dataset queries data, and search_disaster_links finds cross-disaster relationships. No overlap.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case: get_catalog, get_pack, query_dataset, search_disaster_links. No deviations.

Tool Count4/5

4 tools is appropriate for a focused data discovery and query server. Slightly lean but covers essential operations without being too few.

Completeness4/5

Covers discovery (catalog, pack metadata) and querying (dataset, cross-disaster search). Minor gaps such as lack of specific flood event detail endpoint, but query_dataset handles it.

Available Tools

4 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

Behavior4/5

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

Annotations already declare readOnlyHint=true, making safety clear. Description adds useful context that the list is 'live agent-ready' and from DaedalMap, which goes beyond annotations.

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?

Two short sentences with minimal redundancy. 'Free discovery' is slightly redundant with the second sentence, but overall concise and front-loaded.

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?

For a simple list retrieval with no parameters and no output schema, the description adequately states what is returned and from where. Some missing details on data pack format, but acceptable given tool simplicity.

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?

No parameters exist, and schema coverage is 100%, so description doesn't need to add parameter details. Baseline of 4 is appropriate.

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?

Description clearly states it returns a list of data packs, with specific verb 'Returns' and resource 'list of live agent-ready data packs'. However, it does not explicitly differentiate from siblings like get_pack or query_dataset.

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?

Only implies usage via 'Free discovery' but provides no explicit guidance on when to use this tool vs alternatives like get_pack or query_dataset. Missing context for proper selection.

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 such as 'currency', 'earthquakes', 'floods', 'hurricanes', 'tornadoes', 'tsunamis', 'un_sdg', 'volcanoes', 'world_factbook', or 'worldpop'.
Behavior4/5

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

Annotations declare readOnlyHint=true, and the description does not contradict this. It adds behavioral context like 'Free discovery' and specifies the data returned, beyond what annotations provide.

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, no filler. Key purpose ('Free discovery') is first, then details, then usage guidance. Every sentence adds value.

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 no output schema, the description explains what is returned (metadata, coverage, freshness, guidance, examples) and why to use it. It could mention linking to query_dataset but is adequate for a simple tool.

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% with a clear description of pack_id including examples. The description adds no additional parameter semantics beyond stating it identifies the pack.

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 'Returns detailed metadata, coverage, freshness, preferred canonical tool guidance, and first-query examples for one pack.' It distinguishes itself from siblings (get_catalog lists packs, query_dataset queries data) by focusing on single-pack discovery.

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 instructs 'Call this before querying a new pack' and explains benefits: 'see time shape, coverage limits, and the paste-ready first query.' Does not mention when not to use or alternatives, but the context is sufficient.

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: boundaries, currency, distributed_manufacturing, floods, geography, nri, owid, reverse-geocoding, 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 such as 'currency', 'earthquakes', 'floods', 'hurricanes', 'tornadoes', 'tsunamis', 'un_sdg', 'volcanoes', 'world_factbook', or 'worldpop'.
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.
Behavior4/5

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

Annotations declare readOnlyHint=true, consistent with a query tool. The description adds context about the API contract ('same contract as POST /api/v1/query/dataset'), which aids understanding. It does not contradict annotations, and provides pricing info for paid packs, adding behavioral context beyond annotations.

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 the core action and quickly moves to enumerating packs. It is efficient, though the list of packs is somewhat lengthy. No extraneous information; every sentence earns its place.

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?

Given 8 parameters (with nested objects), no required params, and no output schema, the description provides a high-level overview and pricing but lacks details on output format, error handling, or how to construct complex filters. It is minimally adequate but leaves gaps for a new agent.

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?

Schema coverage is 100%, but the description adds value by listing free vs paid packs explicitly, including cost for paid packs (e.g., 'x402 Base USDC'). This information is not present in the schema descriptions, helping an agent decide which pack_id to use.

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: a generic structured query for direct source_id or pack_id access using a specific API contract. It distinguishes from sibling tools (get_catalog, get_pack, search_disaster_links) which are metadata-oriented, making this the go-to for data retrieval.

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 usage when you have a source_id or pack_id and need to query data, but it lacks explicit guidance on when NOT to use or how it compares to alternatives. It does list free vs paid packs, which helps with selection, but no direct exclusion criteria.

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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