Tableau Knowledge MCP

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Add semantic context

create_semantic_context

Attach business context statements to a specific knowledge graph node or the entire graph to document definitions and reporting rules.

Instructions

WRITE: attach business context (one or more statements, 5-1000 characters each) to the knowledge graph, e.g. "Net Sales excludes returns and is reported in EUR."

Set exactly ONE of: `target_node_id` (an exact node id from search_nodes/get_node; the
context then DESCRIBES that node) or `is_global=true` (applies to the whole graph).
CONNECTION, SITE, SCHEMA and semantic-context nodes can't be targets. Some sites accept only
graph-wide context through the API (error node_semantic_context_disabled): then use
is_global=true and name the field or data source in each statement. `name` is optional
(derived when omitted). Needs the Creator role. Returns the new context, with its id.

Input Schema

Name	Required	Description	Default
`name`	No
`graph_id`	No
`is_global`	No
`statements`	Yes
`target_node_id`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 30, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations cover the safety profile (not read-only, non-idempotent, non-destructive), and the description adds what they cannot: the Creator role requirement, the statement length bounds (5-1000 chars), the target-node type restrictions, the specific API error and its workaround, and the return shape ("Returns the new context, with its id"). No contradiction with the declared hints.

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?

Front-loaded with the WRITE marker, then the mutual-exclusion rule, then the edge cases and permission note — every sentence carries information. The third block packs target restrictions, an error code, and a workaround into one dense passage, which slightly hurts scanability but not correctness.

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 detailed, yet the description still notes the returned id. The one genuine hole is graph_id: with is_global and target_node_id both explained, an agent has no idea when graph_id is required or how it interacts with the other two.

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 0%, so the description must carry the load, and it does for four of five parameters: statements (with size bounds and an example), target_node_id (with sourcing guidance from search_nodes/get_node), is_global (whole-graph scope), and name (optional, auto-derived). graph_id is never mentioned, leaving one parameter with no explanation anywhere.

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?

Opens with an explicit verb+resource+mode marker ("WRITE: attach business context ... to the knowledge graph") and gives a concrete example statement, so the effect is unambiguous. It is clearly distinguishable from its update_semantic_context / delete_semantic_context / search_semantic_contexts siblings.

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?

States the exclusivity rule outright ("Set exactly ONE of: target_node_id ... or is_global=true"), enumerates the node types that cannot be targets, and provides a concrete fallback path when the API rejects site-scoped context (error node_semantic_context_disabled). This is explicit when/when-not guidance with an error-driven alternative.

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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