servicenow-mcp-ai

List ServiceNow tables

servicenow_list_tables

Read-onlyIdempotent

Retrieve ServiceNow tables from sys_db_object, optionally filtered by a name or label fragment, to identify available tables for queries or integrations.

Instructions

List tables from sys_db_object, optionally filtered by a name or label fragment.

Input Schema

Name	Required	Description	Default
`filter`	No	Case-insensitive name or label fragment.
`instance`	No	Profile (default active)

Output Schema

Name	Required	Description	Default
`count`	Yes
`tables`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed6 schema fields changedv3.0.0Oct 21, 2026

removedInput schema / $schema

Removed value: -"http://json-schema.org/draft-07/schema#"

changedInput schema / properties / filter / description

Previous value: -"Case-insensitive fragment to match in name or label."New value: +"Case-insensitive name or label fragment."

addedInput schema / properties / filter / maxLength
```
Added value: +255
```

changedInput schema / properties / instance / description

Previous value: -"Connection profile to use for this call (default: the active profile). See servicenow_list_instances."New value: +"Profile (default active)"

addedInput schema / properties / instance / maxLength
```
Added value: +128
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": {},
+  "properties": {
+    "count": {
+      "type": "number"
+    },
+    "tables": {
+      "type": "array"
+    }
+  },
+  "required": [
+    "count",
+    "tables"
+  ],
+  "type": "object"
+}

First observedv2.0.1Sep 5, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations already declare readOnly, idempotent, and non-destructive, so the safety profile is covered without the description's help. The description adds only that results come from sys_db_object; it says nothing about result volume, pagination, or whether the full catalog is returned, which matters for a catalog-listing tool.

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?

One short sentence with no filler, and the source table is front-loaded before the optional filter clause. It is tight, though arguably too terse to carry routing information for a 20-sibling toolkit.

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 need not be explained, and the filter semantics are covered. The remaining gap is that it never positions itself in the discovery workflow relative to describe_table/query_table, but for a simple two-optional-param read tool this is close to complete.

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 both parameters are already documented in the schema, including the case-insensitivity of the filter. The description's 'name or label fragment' restates the schema rather than adding matching semantics or examples beyond it, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb plus resource ('List tables') and it even names the backing table, sys_db_object, which tells an agent exactly what universe of results to expect. It does not, however, distinguish itself from close siblings like servicenow_describe_table or servicenow_query_table, so the agent must infer that this is metadata discovery rather than data retrieval.

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

Usage Guidelines3/5

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

The phrase 'optionally filtered by a name or label fragment' implies the discovery use case (search for a table before querying it), but there is no explicit when-to-use statement and no mention of when to prefer servicenow_describe_table or servicenow_query_table instead. Usage is inferable rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.