Skip to main content
Glama
openl-tablets

OpenL MCP Server

Official

openl Get Table

openl_get_table
Read-onlyIdempotent

Retrieve detailed information about a specific table or rule, including signature, conditions, and row data. Optionally get an unparsed 2D cell matrix for custom table types.

Instructions

Get detailed information about a specific table/rule. By default returns a parsed table structure with signature, conditions, actions, dimension properties, and row data. Set raw=true to get an unparsed 2D cell matrix (RawTableView) instead — useful for unknown/custom table types or preserving exact cell layout. Note: raw output cannot be passed directly to openl_update_table (which expects the parsed form).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID returned by backend. Use the exact 'projectId' value from openl_list_projects() response without modification or reformatting.
tableIdYesTable identifier - unique ID assigned by OpenL Studio when table is created (e.g., 'calculatePremium_1234')
rawNoIf true, returns the raw table view as a 2D matrix of cells without any parsing or structure interpretation. Useful for reading tables of unknown or custom types, preserving exact cell positioning and merge regions.
response_formatNoResponse format: 'json' for structured data, 'markdown' for human-readable (default), 'markdown_concise' for brief summary (1-2 paragraphs), 'markdown_detailed' for full details with contextmarkdown
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, indicating safe read. The description adds behavioral context: raw output is not suitable for updating, and the default parsed form includes signature, conditions, actions, etc. No contradictions with 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 with no redundancy. The first sentence states the main function, the second explains the optional raw mode and its limitation. Every word earns its place.

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 parameter count and lack of output schema, the description compensates by listing what the parsed output includes (signature, conditions, actions, etc.) and detailing raw mode behavior. No gaps left for a read-only retrieval tool.

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?

All four parameters have descriptions in the schema (100% coverage). The description adds meaning for the raw parameter (purpose and limitation) but does not elaborate on projectId/tableId beyond schema or mention response_format. Baseline 3 with minor added value.

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 it retrieves detailed information about a specific table/rule, distinguishing it from sibling tools like openl_list_tables (list tables) and openl_update_table (modify table). It explains two modes: parsed structure (default) and raw cell matrix.

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 when to use raw=true (unknown/custom table types, preserving exact layout) and notes that raw output cannot be passed to openl_update_table, providing clear use-case guidance. However, it does not explicitly compare with all siblings or exclude other scenarios.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/openl-tablets/openl-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server