socrata-mcp-server

Query DataCanvas Table

socrata_dataframe_query

Read-onlyIdempotent

Run SELECT-only SQL against a DataCanvas table populated by socrata_query_dataset. Columns SODA types as number (including aggregate aliases like count(*) as n) are staged as DOUBLE, so numeric comparisons work without a cast (year > 2020, amount < 500). Text and timestamp columns stay VARCHAR — compare times with CAST(date AS TIMESTAMP). Only works when CANVAS_PROVIDER_TYPE=duckdb is set. Use socrata_dataframe_describe to see registered tables and their schemas.

Input Schema

TableJSON Schema

Name	Required	Description
`sql`	Yes	SELECT-only SQL to run against registered canvas tables. DDL, DML, and file-reading functions are rejected. Use table names from socrata_dataframe_describe.
`limit`	No	Max rows to return (1–10000). Default 1000.
`canvas_id`	Yes	Canvas ID returned from socrata_query_dataset or socrata_dataframe_describe.

Output Schema

TableJSON Schema

Name	Required	Description
`cap`	No	The row limit that was applied when capped.
`sql`	No	SQL that was executed.
`rows`	No	Query result rows. DuckDB may return native JS types (number, boolean, null) for numeric/boolean columns.
`error`	No	Present when the call failed. Absent on success.
`shown`	No	Rows returned in this response when capped.
`notice`	No	Guidance when the SQL returned zero rows. Absent when rows are present.
`canvas_id`	No	Canvas ID queried.
`row_count`	No	Number of rows returned.
`truncated`	No	True when results were capped at the limit — more rows match the query.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 20, 2026
- addedInput schema / properties / canvas_id / pattern
```
Added value: +"^[A-Za-z0-9_-]{10}$"
```

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": [
+      "rows",
+      "row_count",
+      "sql",
+      "canvas_id"
+    ]
+  },
+  {
+    "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_disabled`: CANVAS_PROVIDER_TYPE is not set to duckdb — DataCanvas is unavailable. `canvas_not_found`: canvas_id does not match any registered canvas. `table_not_found`: The SQL referenced a canvas table that does not exist — expired, dropped, or a mistyped name. `sql_rejected`: SQL was not a SELECT statement, referenced a system catalog, or contained disallowed functions. Other values are possible when a failure originates below the handler.",
+          "examples": [
+            "canvas_disabled",
+            "canvas_not_found",
+            "table_not_found",
+            "sql_rejected"
+          ],
+          "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: -[
-  "rows",
-  "row_count",
-  "sql",
-  "canvas_id"
-]

Changed3 schema fields changedJun 12, 2026

addedOutput schema / properties / cap

Added value: +{
+  "description": "The row limit that was applied when capped.",
+  "type": "number"
+}

addedOutput schema / properties / shown

Added value: +{
+  "description": "Rows returned in this response when capped.",
+  "type": "number"
+}

addedOutput schema / properties / truncated

Added value: +{
+  "description": "True when results were capped at the limit — more rows match the query.",
+  "type": "boolean"
+}

Changed1 schema field changedMay 30, 2026

addedOutput schema / properties / notice

Added value: +{
+  "description": "Guidance when the SQL returned zero rows. Absent when rows are present.",
+  "type": "string"
+}

First observedMay 25, 2026

TDQS

A4.7/5.0

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 valuable behavioral context: SELECT-only enforcement, rejection of DDL/DML/file-reading functions, type staging behavior (numbers as DOUBLE, text/timestamps as VARCHAR), and the need for CAST for timestamp comparisons. This goes beyond the annotations and helps the agent predict execution behavior.

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?

The description is compact and front-loaded with the core action ('Run SELECT-only SQL'), then adds the most important behavioral caveats (type staging, provider requirement) and a pointer to the sibling tool. Every sentence earns its place; no filler or repetition of schema details.

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 the output schema exists and the annotations cover safety, the description is complete for an agent to select and invoke the tool correctly. It covers prerequisites, constraints, type behavior, and how to discover table names. The only minor gap is not describing the output format, but the output schema handles that.

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 description coverage is 100%, so the schema already documents all three parameters. The description adds meaning by explaining the type-staging behavior that affects how parameters like sql should be written (e.g., numeric comparisons work without cast, timestamps need CAST). It also reinforces that table names come from socrata_dataframe_describe, which is useful context beyond the schema.

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 states a specific verb ('Run SELECT-only SQL') and a specific resource ('a DataCanvas table populated by socrata_query_dataset'), and it distinguishes itself from siblings by naming socrata_dataframe_describe for schema discovery. It clearly identifies what the tool does and how it differs from related tools.

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 says when to use this tool (after socrata_query_dataset populates a table) and when not to (only works when CANVAS_PROVIDER_TYPE=duckdb is set). It also points to socrata_dataframe_describe for registered tables and schemas, giving the agent a clear alternative and prerequisite.

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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