Skip to main content
Glama

list_available_tools

List capability names that can be granted to agents. Use this before creating an agent to choose the right permissions for your workflow.

Instructions

List capability names that can be granted to agents.

Use before create_agent to choose the capabilities argument. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed5 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / title
      Removed value: -"list_available_toolsArguments"
    • removedOutput schema / properties / result / title
      Removed value: -"Result"
    • removedOutput schema / title
      Removed value: -"list_available_toolsOutput"
    • addedOutput schema / x-fastmcp-wrap-result
      Added value: +true
  2. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It explicitly states 'Read-only,' which is a meaningful behavioral trait for an agent to know. It does not cover auth or rate limits, but for a simple list operation this is sufficient.

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 short sentences with zero wasted words. The core action is front-loaded, followed by a concrete usage instruction and a read-only note. Every sentence 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 zero parameters and an output schema, the description is fully complete for an agent to select and invoke this tool correctly. It explains what it lists, why an agent would use it, and that it has no side effects.

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 tool has zero parameters and the schema coverage is 100%, so the baseline is 4. The description adds relevant context by explaining that the output is meant for the 'capabilities argument' in create_agent, which is helpful even though there are no parameters to document.

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 states a specific verb ('List') and resource ('capability names that can be granted to agents'), which clearly distinguishes it from siblings like list_agents and create_agent. The purpose is immediately understandable without needing to inspect schemas.

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?

The description explicitly says to use this tool before create_agent to choose the capabilities argument, giving clear contextual guidance. It does not mention when not to use it or compare it to alternatives, but the intended workflow is unambiguous.

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

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/ANAMIZED/OpenMesha'

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