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exchange-rates-mcp-server

by io.github.cyanheads
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Fx Dataframe Describe

fx_dataframe_describe
Read-onlyIdempotent

List tables and columns staged on a DataCanvas from a prior fx_get_timeseries call. Required first step before fx_dataframe_query — use it to discover table names and column schemas. Requires DataCanvas (CANVAS_PROVIDER_TYPE=duckdb) — without it this tool is not listed at all and fx_get_timeseries returns every range inline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
canvas_idYesCanvas ID returned by fx_get_timeseries. Re-run fx_get_timeseries to obtain a fresh canvas_id if this one has expired.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
tablesNoAll tables and views currently staged on this canvas.
canvas_idNoThe canvas ID echoed back — use this in fx_dataframe_query.
expires_atNoISO 8601 timestamp when this canvas will be evicted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / canvas_id / pattern
      Added value: +"^[A-Za-z0-9_-]{10}$"
  2. Changed6 schema fields changed
    • 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",
+      "expires_at"
+    ]
+  },
+  {
+    "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 exist or has been evicted. 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",
-  "expires_at"
-]
  3. First observed

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, and the description adds non-obvious context: the tool only exists when CANVAS_PROVIDER_TYPE=duckdb, and without it fx_get_timeseries returns every range inline. This goes beyond the structured annotations by explaining environmental dependencies and consequences.

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?

Three sentences with no filler: purpose is front-loaded, usage guidance follows, and the prerequisite/environment note is last. Every sentence adds distinct value.

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?

For a single-parameter, read-only discovery tool with an output schema and complete annotations, the description covers purpose, when to use it, how to get the parameter, and what happens without the required environment. No important calling context 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?

Schema description coverage is 100%, and the canvas_id parameter is already documented as returned by fx_get_timeseries with expiry guidance. The tool description repeats the relationship to fx_get_timeseries but adds no parameter-level detail beyond the schema, so 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 opens with a specific verb and resource: 'List tables and columns staged on a DataCanvas from a prior fx_get_timeseries call.' It also distinguishes the tool from fx_dataframe_query by explicitly positioning it as the required discovery step, so an agent can tell when this tool applies.

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 states exactly when to use it ('Required first step before fx_dataframe_query') and what to use it for ('discover table names and column schemas'). It also names the prerequisite DataCanvas environment and explains the fallback behavior when the prerequisite is absent, making the selection rules explicit.

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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