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Glama

Call a tool on a server

call_tool
Destructive

Invoke any tool from the MCP hub's connected servers by specifying server, tool name, and arguments matching the input schema.

Instructions

Call a tool on one of the MCP servers. Arguments must match the schema from get_tool_schema.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesTool name from list_tools
serverYesServer name from list_servers
argumentsNoTool arguments matching its input schema

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.11.2
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedInput schema / properties / arguments / additionalProperties
      Previous value: -{}New value: +true
  2. First observedv0.9.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already indicate destructiveHint: true and readOnlyHint: false, so the description need not repeat them. The description adds minimal behavioral context beyond input validation, and does not mention potential side effects or errors. It is not contradictory, but does not enrich the annotation-provided behavioral profile.

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?

The description is extremely concise, consisting of two short sentences. It conveys the essential purpose and a key constraint without any fluff, making it easy for an agent to parse quickly.

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?

Given that there is no output schema, the description appropriately focuses on input requirements. It references get_tool_schema for argument validation, which is helpful context. It does not mention return behavior, but that is acceptable since the tool simply returns the result of the called tool, and the description is sufficient for an agent to invoke it correctly.

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?

The schema provides complete descriptions for all three parameters (tool, server, arguments) with 100% coverage. The description adds no additional semantic meaning beyond restating that arguments must match the schema, which is already evident from the parameter name and description. Thus the baseline score of 3 applies.

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 the action ('Call a tool') and the resource ('on one of the MCP servers'), and explicitly ties arguments to get_tool_schema. It is distinct from siblings like list_servers or get_tool_schema, making the purpose unambiguous.

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?

It implicitly guides usage by stating that arguments must match the schema from get_tool_schema, suggesting a prerequisite. However, it does not explicitly state when to choose this tool over alternatives (e.g., when to use list_tools vs call_tool), leaving some room for inference.

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