Skip to main content
Glama

create_workspace

Create a new workspace to organize pipelines, indexes, and other resources. Provide a unique name to set up an isolated environment for deploying pipelines.

Instructions

Creates a new workspace with the specified name.

This tool creates a new workspace that can be used to organize pipelines, indexes, and other resources. The workspace name must be unique across the platform. Once created, you can start deploying pipelines and other resources within this workspace. :param name: The name for the new workspace. Must be unique. :returns: Success confirmation or error message.

The output is automatically stored and can be referenced in other functions. Returns a formatted preview with an object ID (e.g., @obj_123). Use the object store tools in combination with the object ID to view nested properties of the object. Use the returned object ID to pass this result to other functions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
Behavior4/5

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

With no annotations, the description carries full burden. It discloses the mutation (creates), uniqueness constraint, usage after creation, and output format (object ID and preview). This adds useful behavioral context beyond merely stating the action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with paragraphs and docstring elements, but includes redundant statements (e.g., 'The output is automatically stored...' and 'Returns a formatted preview...'). It could be more concise while retaining key information.

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?

For a simple one-parameter tool with no output schema, the description covers purpose, parameter uniqueness, output format, and how to use the result. It is mostly complete, though it omits error behavior when the name already exists.

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?

The schema has 0% coverage for parameter descriptions, so the description compensates by explaining that the name must be unique across the platform, adding meaning beyond the schema's bare 'Name' field.

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?

The description clearly states it creates a new workspace with a specified name, and contrasts with siblings like create_index and create_pipeline by noting that workspaces organize pipelines and indexes. However, it does not explicitly differentiate from other create tools.

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 description implies usage for creating a workspace to organize resources, but does not provide explicit when-to-use, when-not-to-use, or alternative tool guidance. No exclusions or comparisons to siblings are given.

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/deepset-ai/deepset-mcp-server'

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