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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

grant_permission

Grant access to a database, schema, or object by assigning permissions to a principal. Supports column-level security and with grant option.

Instructions

Grant permissions on a securable to a principal.

Executes GRANT <permissions> ON <scope> TO <principal>. Blocked by FABRIC_MCP_READONLY. Does NOT require FABRIC_MCP_ALLOW_DESTRUCTIVE.

Args: workspace: Workspace name or GUID. item: Warehouse or SQL endpoint name or GUID. permissions: Comma-separated permission tokens (e.g. "SELECT,INSERT"). principal: Grantee principal name (Entra UPN, app GUID, or role name). scope: Securable class -- "DATABASE" (default), "SCHEMA", or "OBJECT". schema: Schema name (required when scope is "SCHEMA"). object_name: Qualified object name <schema>.<object> (required when scope is "OBJECT"). with_grant_option: When True, allows the grantee to grant the permission to others (adds WITH GRANT OPTION). columns: Optional list of column names for column-level security (OBJECT scope only; permissions must be SELECT, UPDATE, or REFERENCES). Pass None (omit) for no column restriction. Passing an empty list raises a ToolError.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemYes
scopeNoDATABASE
schemaNo
columnsNo
principalYes
workspaceYes
object_nameNo
permissionsYes
with_grant_optionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description reveals behavior: it is a write operation blocked by readonly, non-destructive per the flag absence, and describes error behavior for empty columns list.

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?

The description is well-structured with a lead paragraph and bulleted arg list. It is slightly long but front-loaded with purpose and SQL equivalent. Efficient overall.

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 complexity of the tool (9 params, no annotations, but output schema exists), the description covers all necessary details: parameter usage, error cases, and safety flags. It is fully sufficient for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description fully explains all 9 parameters with constraints, defaults, and special behaviors (e.g., column restrictions, required schema for SCHEMA scope), adding substantial value 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 clearly states 'Grant permissions on a securable to a principal', provides the SQL equivalent, and the tool name and title differentiate it from siblings like deny_permission and revoke_permission.

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 specifies blocking by FABRIC_MCP_READONLY and that FABRIC_MCP_ALLOW_DESTRUCTIVE is not required, giving usage constraints. It also details parameter dependencies (e.g., schema required when scope is SCHEMA). However, it does not explicitly compare to alternatives.

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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