Skip to main content
Glama

embed

Convert text to vector embeddings for semantic search and knowledge organization in Obsidian vaults and local knowledge systems.

Instructions

Get embedding for text

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
Behavior2/5

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

No annotations are provided, yet the description fails to disclose critical behavioral traits: the embedding model used, output format/structure (vector array dimensions), rate limits, or whether the operation is deterministic. The description carries the full disclosure burden and provides minimal information.

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 four-word description contains no redundancy, but conciseness here manifests as under-specification rather than efficient precision. Given the complete absence of schema descriptions and annotations, this level of brevity is inappropriate.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, no annotations, and zero parameter description coverage, the tool description bears full responsibility for explaining return values and behavior. It fails to do so, providing insufficient context for safe and effective invocation.

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

Parameters2/5

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

With 0% schema description coverage, the description must compensate for the undocumented 'text' parameter. While it implies the parameter contains input text, it fails to specify constraints, expected format, encoding, or maximum length, leaving critical semantic gaps.

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

Purpose3/5

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

The description provides a specific verb ('Get') and resource ('embedding') but remains vague regarding the embedding type (vector, semantic, etc.) and does not explicitly differentiate from siblings, though the operation is implicitly distinct from the file and calculation tools listed.

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

Usage Guidelines2/5

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

No guidance is provided regarding when to use this tool versus alternatives, prerequisites (e.g., text length limits), or expected use cases. The description states what it does but not when to invoke it.

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/KVANTRA-dev/NOUZ-MCP'

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