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unhcr-refugees-mcp-server

by io.github.cyanheads
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Describe staged dataframes

unhcr_dataframe_describe
Read-onlyIdempotent

Describe a dataframe (df_XXXXX_XXXXX) staged by the unhcr_get_* tools — any response carrying a dataset handle staged its full result here — or list them all where this deployment allows listing. Each entry gives the source tool, query parameters, creation and expiry time, row count, whether the upstream fetch was complete, and the column schema. Read the columns here before writing SQL for unhcr_dataframe_query.

Input Schema

NameRequiredDescriptionDefault
nameNoOne dataframe to describe, as df_XXXXX_XXXXX (uppercase letters and digits): the dataset.name a unhcr_get_* result returned, or a register_as name. Omit to list every staged dataframe; a deployment that serves unauthenticated callers over HTTP turns listing off, and there the name is required.

Output Schema

NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
noticeNoGuidance when nothing is staged or the named dataframe is gone.
dataframesNoStaged dataframes, newest first. Empty when none are staged.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedOutput schema / properties / dataframes / items / properties / incomplete_sources
      Added value: +{
+  "description": "Original incomplete upstream handles retained through saved descendants, even after those ancestors expire or are evicted.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • changedOutput schema / properties / dataframes / items / required
      Previous value: -[
-  "name",
-  "source_tool",
-  "query_params",
-  "created_at",
-  "expires_at",
-  "row_count",
-  "complete",
-  "providers",
-  "column_schema"
-]New value: +[
+  "name",
+  "source_tool",
+  "query_params",
+  "created_at",
+  "expires_at",
+  "row_count",
+  "complete",
+  "incomplete_sources",
+  "providers",
+  "column_schema"
+]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavior: staged results expire, listing can be disabled in unauthenticated HTTP deployments, and completeness of the upstream fetch is surfaced. It does not mention pagination or size limits, keeping it short of 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded and the two sentences are dense with useful content. The opening sentence is somewhat convoluted with its em-dash aside ('— any response carrying a dataset handle staged its full result here —'), but nothing is padding.

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?

An output schema exists, so return values needn't be explained, yet the description enumerates the entry fields (source tool, query params, creation/expiry, row count, completeness, column schema), which is slightly redundant but helps the agent know what it can rely on. The full describe→query workflow is covered.

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% and the single 'name' parameter is fully documented in the schema, including the pattern and the listing fallback. The description restates the staging origin (dataset.name / register_as name) and the listing-off case rather than adding new syntax or format detail, 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+resource ('Describe a dataframe (df_XXXXX_XXXXX) staged by the unhcr_get_* tools') and explicitly names the sibling it feeds into (unhcr_dataframe_query). An agent can distinguish it from the query tool and from the unhcr_get_* producers without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit routing: 'Read the columns here before writing SQL for unhcr_dataframe_query.' It also states the when-not condition — omit name to list, but name is required in deployments serving unauthenticated HTTP callers. Both the action and the exclusion are spelled out.

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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