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marsaplatform

Malja MCP

Official

Situation reports

situation_reports
Read-only

Fetch yearly counts of ReliefWeb humanitarian reports for a country plus recent report titles and links, with text and date filters, to ground reported trends and anomalies.

Instructions

Situation reports published about a country: yearly counts plus the most recent report titles and links (ReliefWeb). Use it to ground trends and anomalies from other tools in what was actually reported at the time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoFree-text filter for the listed reports (e.g. "cholera") — yearly counts stay unfiltered
localeNoLanguage of the human-readable text output: "en" (default) or "ar" (Modern Standard Arabic, right-to-left). Structured JSON fields, ISO3 codes and dataset ids stay in English either way.
countryYesCountry name or ISO3 code, e.g. "Egypt", "EGY", "syria"
year_toNoLast year of the range (default: latest available)
year_fromNoFirst year of the range (default: 10 years back)
max_reportsNoHow many of the most recent reports to list (default 5)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
latestYes
sourceYes
countryYes
recordsYes
country_codeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile and external-source nature are partly covered. The description adds the provenance (ReliefWeb) and the fact that the returned titles/links are 'most recent', which is useful context, but says nothing about rate limits, coverage gaps, or freshness lag beyond that.

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, zero filler: the first front-loads what is returned and the second supplies the usage rationale. Every clause earns its place.

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 an output schema present, the description need not explain return values, and annotations cover the read-only/open-world profile. It states source and purpose adequately; only the relationship to the many sibling analysis tools remains slightly underspecified.

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% and all six parameters, including the locale enum and the year/max_reports bounds, are documented in the schema itself. The description adds no additional parameter meaning (e.g. it never clarifies the query filter or the year defaults), so the baseline of 3 applies.

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 names a specific resource ('situation reports published about a country') and precisely enumerates the payload ('yearly counts plus the most recent report titles and links'), even citing the source (ReliefWeb). It does not explicitly contrast itself with any sibling tool, so it stops short of the top tier, but an agent can still tell what it returns without opening the schema.

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?

'Use it to ground trends and anomalies from other tools in what was actually reported at the time' gives a clear situational trigger and implies it complements rather than replaces analysis tools like trend_analysis or conflict_events. It gives no explicit when-not or named alternative, so it is clear context without exclusions.

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