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musharna

data-aggregator-mcp

by musharna
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_sources

Read-only

Lists wired research data sources with capabilities, supported filters, auth needs, rate limits, and status; optionally probes five sources for health.

Instructions

List wired data sources and their capabilities (layer, kinds, supported filters, auth requirement, rate limit, status). filters_supported names the search parameters a source applies itself: cursor = it pages past page 1; published_after/published_before/kind = filtered upstream, so its total is filtered (any other source is filtered after fetch); organism/disease/tissue/chemical/assay = the synonym expansion reaches its query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
check_healthNoWhen true, probe 5 sources (zenodo, datacite, omics, literature, huggingface) and attach a 'health' field ({status: up|down, latency_ms, detail}) to those entries; every other source gets health: null. Default false: returns the static catalog with no network.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourcesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.54.1
    • addedInput schema / additionalProperties
      Added value: +false
  2. Changed1 schema field changedv0.42.0
    • changedInput schema / properties / check_health / description
      Previous value: -"When true, probe 5 sources (zenodo, datacite, omics, literature, huggingface) and attach a 'health' field ({status: up|down, latency_ms, detail}) to those entries; the remaining 7 sources get health: null. Default false: returns the static catalog with no network."New value: +"When true, probe 5 sources (zenodo, datacite, omics, literature, huggingface) and attach a 'health' field ({status: up|down, latency_ms, detail}) to those entries; every other source gets health: null. Default false: returns the static catalog with no network."
  3. Changed1 schema field changedv0.40.0
    • changedInput schema / properties / check_health / description
      Previous value: -"When true, probe each source's base endpoint and attach a 'health' field ({status: up|down, latency_ms, detail}) to each source. Default false: returns the static catalog with no network."New value: +"When true, probe 5 sources (zenodo, datacite, omics, literature, huggingface) and attach a 'health' field ({status: up|down, latency_ms, detail}) to those entries; the remaining 7 sources get health: null. Default false: returns the static catalog with no network."
  4. Changed1 schema field changedv0.16.0
    • addedInput schema / properties / check_health
      Added value: +{
+  "default": false,
+  "description": "When true, probe each source's base endpoint and attach a 'health' field ({status: up|down, latency_ms, detail}) to each source. Default false: returns the static catalog with no network.",
+  "type": "boolean"
+}
  5. First observedv0.11.0

TDQS

A4/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true, and the description adds real behavioral context beyond that: which filter values are applied upstream by a source versus 'after fetch', and that some sources have auth and rate-limit constraints. It stops short of describing the tool's own failure modes or cost of the network probe, which the schema covers instead.

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?

Purpose is front-loaded in a short first sentence; the second sentence is dense but every clause (cursor, date/kind, synonym-expansion filters) earns its place by defining a returned field's values. The semicolon-chained list is slightly run-on but not wasteful.

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?

With an output schema present and the single parameter fully documented in the schema, the description supplies what structured fields cannot: the semantics of filters_supported values. Nothing an agent needs to call this correctly is missing.

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?

There is one parameter and schema description coverage is 100%, so the schema already fully documents check_health, including which five sources are probed and the health field shape. The description adds nothing about it, so the baseline 3 applies.

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?

States a specific verb and resource ('List wired data sources') and enumerates exactly what each entry carries (layer, kinds, filters, auth requirement, rate limit, status). No sibling tool (search/operate/resolve/fetch/relate) overlaps with enumerating sources, so the scope is unmistakable.

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?

Usage is only implied: an agent can infer this is the discovery step before querying, but the description never says when to call it versus running a search directly, nor when to re-list. The filters_supported explanation helps interpret results but is not a when-to-use instruction.

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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