secedgar-mcp-server

Secedgar Dataframe Describe

secedgar_dataframe_describe

Read-onlyIdempotent

List the dataframes (df_XXXXX_XXXXX) registered by the data-returning secedgar_* tools — any tool whose response carries a dataset handle stages its full result set here. Each entry surfaces source tool, query parameters, creation/expiry timestamps, row count, column schema, and whether the dataframe is truncated relative to the upstream source. Read the column schema here before writing SQL for secedgar_dataframe_query.

Input Schema

Name	Required	Description	Default
`name`	No	Optional table name (df_XXXXX_XXXXX) to describe a single dataframe. Omit to list all dataframes.

Output Schema

Name	Required	Description	Default
`error`	No	Present when the call failed. Absent on success.
`dataframes`	No	Active dataframes for this tenant, newest first. Empty when none are registered.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 26, 2026

changedOutput schema / properties / dataframes / items / properties / expires_at / description

Previous value: -"ISO 8601 expiry timestamp. Sliding TTL touched on every dataframe op."New value: +"ISO 8601 expiry timestamp, fixed when the table is staged; queries do not extend it."

Changed1 schema field changedSep 22, 2026

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

Previous value: -"Machine-readable failure mode. Declared by this tool: `canvas_unavailable`: The DataCanvas service is not configured for this deployment Other values are possible when a failure originates below the handler."New value: +"Machine-readable failure mode. Declared by this tool: `canvas_unavailable`: The DataCanvas service is not configured for this deployment. Other values are possible when a failure originates below the handler."

Changed6 schema fields changedAug 22, 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": [
+      "dataframes"
+    ]
+  },
+  {
+    "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_unavailable`: The DataCanvas service is not configured for this deployment Other values are possible when a failure originates below the handler.",
+          "examples": [
+            "canvas_unavailable"
+          ],
+          "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: -[
-  "dataframes"
-]
```

AddedMay 17, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already establish read-only, idempotent, closed-world behavior, and the description adds meaningful context: results are staged from data-returning tools, each entry includes source tool, query parameters, timestamps, row count, schema, and truncation status. It does not cover auth or rate limits, but it goes well beyond the annotations.

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, front-loaded with the core purpose, then the entry structure, then the sibling routing. Every sentence carries useful information with no padding.

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?

Given a single optional parameter, full schema coverage, existing annotations, and an output schema, the description provides enough context to call the tool correctly. It explains what is listed and why an agent should consult it before querying.

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%, so the parameter is fully documented in the schema. The description mentions the dataframe naming pattern and listing behavior, but does not add substantial meaning beyond the schema's explanation of omitting `name` to list all dataframes.

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 gives a specific verb and resource: 'List the dataframes (df_XXXXX_XXXXX) registered by the data-returning secedgar_* tools.' It also clarifies the registration mechanism via `dataset` handles, so an agent can distinguish this discovery tool from the SQL querying sibling.

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?

It explicitly routes the agent to this tool before writing SQL for `secedgar_dataframe_query`, which is useful sibling guidance. It does not state when not to use it or mention other alternatives, but the core usage context is clear.

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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