imf-mcp-server

Imf Dataframe Describe

imf_dataframe_describe

Read-onlyIdempotent

List DataCanvas tables and columns staged by a prior imf_query_dataset call. Returns each table's name, row count, and column schema (name + DuckDB type). Required before imf_dataframe_query to discover the table and column names for SQL.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`canvas_id`	Yes	Canvas ID returned by imf_query_dataset whenever staged=true, from automatic spillover or output_mode="canvas".

Output Schema

TableJSON Schema

Name	Required	Description
`error`	No	Present when the call failed. Absent on success.
`tables`	No	All tables registered on this canvas.
`canvas_id`	No	Canvas session ID that was introspected.
`table_count`	No	Total number of tables on the canvas.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 19, 2026

addedInput schema / properties / canvas_id / pattern
```
Added value: +"^[A-Za-z0-9_-]{10}$"
```

changedOutput schema / properties / error / properties / data / properties / reason / description

Previous value: -"Machine-readable failure mode. Declared by this tool: `canvas_not_found`: canvas_id does not match any registered DataCanvas session (expired, wrong session, or canvas disabled) Other values are possible when a failure originates below the handler."New value: +"Machine-readable failure mode. Declared by this tool: `canvas_not_found`: canvas_id does not match any registered DataCanvas session (expired, wrong session, or canvas disabled). Other values are possible when a failure originates below the handler."

Changed1 schema field changedAug 31, 2026

changedInput schema / properties / canvas_id / description

Previous value: -"Canvas ID returned by imf_query_dataset when results were too large for inline delivery."New value: +"Canvas ID returned by imf_query_dataset whenever staged=true, from automatic spillover or output_mode=\"canvas\"."

Changed6 schema fields changedAug 25, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

addedInput schema / additionalProperties
```
Added value: +false
```

changedOutput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

addedOutput schema / anyOf

Added value: +[
+  {
+    "not": {
+      "required": [
+        "error"
+      ]
+    },
+    "required": [
+      "canvas_id",
+      "tables",
+      "table_count"
+    ]
+  },
+  {
+    "required": [
+      "error"
+    ]
+  }
+]

addedOutput schema / properties / error

Added value: +{
+  "additionalProperties": {},
+  "description": "Present when the call failed. Absent on success.",
+  "properties": {
+    "code": {
+      "description": "JSON-RPC error code for this failure.",
+      "maximum": 9007199254740991,
+      "minimum": -9007199254740991,
+      "type": "integer"
+    },
+    "data": {
+      "additionalProperties": {},
+      "properties": {
+        "reason": {
+          "description": "Machine-readable failure mode. Declared by this tool: `canvas_not_found`: canvas_id does not match any registered DataCanvas session (expired, wrong session, or canvas disabled) Other values are possible when a failure originates below the handler.",
+          "examples": [
+            "canvas_not_found"
+          ],
+          "type": "string"
+        },
+        "recovery": {
+          "additionalProperties": {},
+          "description": "Actionable next step for the caller.",
+          "properties": {
+            "hint": {
+              "type": "string"
+            }
+          },
+          "required": [
+            "hint"
+          ],
+          "type": "object"
+        },
+        "retryable": {
+          "description": "Whether retrying may succeed.",
+          "type": "boolean"
+        }
+      },
+      "type": "object"
+    },
+    "message": {
+      "description": "Human-readable description of what went wrong.",
+      "type": "string"
+    }
+  },
+  "required": [
+    "code",
+    "message"
+  ],
+  "type": "object"
+}

removedOutput schema / required

Removed value: -[
-  "canvas_id",
-  "tables",
-  "table_count"
-]

First observedJun 7, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds meaningful behavioral context by clarifying the dependency on a prior imf_query_dataset call and specifying what is returned (table name, row count, column schema). It does not go into pagination or error behavior, but that is minor given the annotations and output schema.

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 with no filler: the first states the action and return content, the second states the prerequisite. The most important operational detail (required before imf_dataframe_query) is placed at the end but is still concise and clearly separated from the functional description.

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?

The description is complete for an introspection tool: it explains what the tool lists, what the output includes, and why an agent needs it before querying. The output schema exists, annotations cover safety, and the single parameter is fully documented. Nothing critical is missing for correct invocation.

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?

The only parameter, canvas_id, is fully documented in the schema with a description that already explains its origin and valid values. The tool description reinforces the staging context but does not add new parameter-level meaning beyond what the schema provides. Since schema coverage is 100%, the baseline of 3 is appropriate.

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?

The description uses a specific verb ('List') and identifies the precise resource: DataCanvas tables and columns staged by a prior imf_query_dataset call. It also clearly differentiates this tool from siblings like imf_dataframe_query and imf_query_dataset by framing it as the discovery step for staged data.

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?

The description explicitly states when to use this tool: 'Required before imf_dataframe_query to discover the table and column names for SQL.' This gives the agent a clear prerequisite relationship and tells it why this tool exists in the workflow.

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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