DaedalMap Population Estimates
Server Details
Global population estimates from WorldPop, 2000-2030, at country and sub-national levels.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
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.
Tool Definition Quality
Average 4.1/5 across 3 of 3 tools scored.
Each tool serves a distinct purpose: get_catalog lists available data packs, get_pack retrieves metadata for a specific pack, and query_dataset performs queries. No functional overlap.
All tool names follow a consistent verb_noun snake_case pattern (get_catalog, get_pack, query_dataset), making them predictable.
Three tools is an appropriate scope for a data discovery and query server, covering the core workflow without unnecessary complexity.
The tool set covers discovery (catalog, pack metadata) and querying, but lacks a tool for listing supported pack IDs or searching packs by keyword, which could be helpful.
Available Tools
3 toolsget_catalogGet CatalogARead-onlyInspect
Free discovery. Returns the list of live agent-ready data packs available on DaedalMap.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description does not need to repeat that. It adds value by noting 'Free discovery' (suggesting low cost/overhead) and 'live agent-ready' (implying real-time availability), which are not captured by annotations.
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?
Single sentence that is front-loaded with key context ('Free discovery') and directly states the output. No wasted words.
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?
Description explains what is returned and the source, but lacks details on the structure of the list (e.g., fields in each pack). For a simple listing with no output schema, more completeness could help an agent understand what to expect.
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?
There are no parameters, and schema coverage is 100%. The description does not need to add parameter details. Baseline for 0 parameters is 4.
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?
Description clearly states it returns a list of live agent-ready data packs from DaedalMap, with a specific verb and resource. It distinguishes from siblings like get_pack (single pack) and query_dataset (data queries) by focusing on catalog discovery.
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 lightweight access but does not explicitly state when to use this tool versus alternatives like get_pack or query_dataset. No exclusions or alternative guidance provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_packGet PackARead-onlyInspect
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.
| Name | Required | Description | Default |
|---|---|---|---|
| pack_id | Yes | Pack identifier such as 'currency', 'earthquakes', 'floods', 'hurricanes', 'tornadoes', 'tsunamis', 'un_sdg', 'volcanoes', 'world_factbook', or 'worldpop'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only; description adds behavioral details like returning coverage, freshness, and first-query examples, which is valuable 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with 'Free discovery', no wasted words. Efficient and clear.
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 single parameter, no output schema, and adequate annotations, description covers necessary information for usage and expectations.
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?
Schema coverage is 100% with parameter description. Description reinforces that it's for one pack, but adds minimal meaning beyond schema.
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?
Description clearly states it returns detailed metadata etc. for one pack. It distinguishes from siblings by recommending use before querying a new 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?
Description explicitly says 'Call this before querying a new pack' and explains why, providing clear usage context. Does not mention exclusions but 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 DatasetARead-onlyInspect
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_co2, reverse-geocoding, un_sdg, un_wpp, volcanoes, world_bank_wdi. Paid packs: earthquakes, hurricanes, tornadoes, tsunamis, wildfires, world_factbook, worldpop (x402 Base USDC).
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Optional sort instructions for row-returning queries. | |
| limit | No | Maximum number of rows to return for the requested source or pack. | |
| output | No | Optional output controls such as response format hints. | |
| filters | No | Structured filters including time, region_ids, and compare clauses. | |
| metrics | No | Metric ids to return. Use event_count for aggregate counts when supported. | |
| pack_id | No | Pack identifier such as 'currency', 'earthquakes', 'floods', 'hurricanes', 'tornadoes', 'tsunamis', 'un_sdg', 'volcanoes', 'world_factbook', or 'worldpop'. | |
| source_id | No | Concrete source id such as 'earthquakes_events', 'volcanoes_events', 'hurricanes_events', or 'un_sdg/01'. | |
| request_id | No | Optional caller-supplied request id for tracing and idempotency. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds valuable behavioral context by listing specific free and paid packs, and mentioning the contract. No contradictions.
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 concise with two self-contained sentences. The first sentence defines purpose, the second lists packs. No fluff, front-loaded.
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's complexity (8 parameters, nested objects, no output schema), the description is fairly complete. It explains the contract and pack availability, and schema covers the rest. Minor gap: no mention of typical output or pagination, but schema handles that.
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?
Schema description coverage is 100%, so parameters are already well-documented. The tool description lists pack and source identifiers again, which is slightly redundant but provides quick reference.
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 performs a generic structured query for direct source_id or pack_id access, and specifies the contract and lists free and paid packs, distinguishing it from sibling tools like get_catalog and get_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 description provides context on free vs paid packs but does not explicitly state when to use this tool versus alternatives or when not to use it. Sibling tool names imply differentiation but no explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!