Malja MCP

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by marsaplatform

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TypeScript

Hybrid

Export data

export_data

Read-only

Export normalized humanitarian datasets as CSV, JSON, Markdown, or GeoJSON for download or reuse. Use it when users need filtered raw records ready to paste elsewhere.

Instructions

Export normalized records from any dataset as csv, json, markdown or geojson (geojson only makes sense with group_by set, so rows map to countries). Use this when the user wants raw data to download or paste elsewhere.

Input Schema

TableJSON Schema

Name	Required	Description
`role`	No	"asylum" = people hosted IN the country; "origin" = people displaced FROM the country
`limit`	No	Max rows (default 500)
`format`	Yes	Serialization format
`locale`	No	Language 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.
`country`	No	Filter by country (name or ISO3)
`dataset`	Yes	population \| demographics \| asylum-applications \| asylum-decisions \| context-indicators \| idps \| conflict-events \| humanitarian-funding \| food-security
`year_to`	No	Last year of the range (default: latest available)
`group_by`	No	Break rows down per asylum or origin country instead of aggregating
`year_from`	No	First year of the range (default: 10 years back)
`include_codebook`	No	Attach a codebook documenting every exported variable (meaning, unit, derivation) — ready for a paper's data appendix. Default false.
`include_manifest`	No	Attach an extraction manifest (exact arguments, timestamp, server version, citation) for reproducibility. Default true.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	Yes
`format`	Yes
`dataset`	Yes
`codebook`	No
`manifest`	No
`row_count`	Yes
`truncated`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.7.0Oct 20, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds a genuinely useful behavioral constraint not in the schema: geojson only makes sense when group_by is set because rows map to countries. It omits other non-obvious behaviors (e.g., manifest attached by default), so not a 5.

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 waste. The format list and the geojson caveat come first, then the usage trigger, so the most decision-relevant information is 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?

With 11 parameters, an output schema, and readOnly/openWorld annotations, the description only needs to resolve format choice, the geojson caveat, and the usage context, which it does. Defaults (limit 500, manifest true) and all field semantics live in the schema, so nothing critical is missing.

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%, so the baseline is 3. The description exceeds that by documenting a cross-parameter interaction — the geojson/group_by coupling — that the schema does not express, adding real meaning beyond the field-level descriptions.

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?

States a specific verb ('Export') plus the resource ('normalized records from any dataset') and enumerates the output formats, including a real caveat about geojson. It does not name or differentiate against the obvious sibling export_report, so an agent must infer the raw-vs-formatted distinction.

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 this when the user wants raw data to download or paste elsewhere" gives a clear usage trigger. However it provides no explicit when-not or names the alternative (export_report), leaving the raw-vs-report boundary to inference.

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