Skip to main content
Glama
EyalSec

EyalSec MCP Server

Official
by EyalSec

Supported targets

supported_targets
Read-onlyIdempotent

Lists supported Linux distributions, architectures, and Python versions for es-python installations, optionally filtered by an OS target such as ubuntu_24_04_x86_64.

Instructions

The Linux distributions, architectures and Python versions es-python can be installed for. Needs no API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
osNoAn OS target such as 'ubuntu_24_04_x86_64' to list only the Python versions for it.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is fully covered by structured data. The description adds one genuine piece of context beyond that — no API key required — but says nothing about caching, freshness, or result size, which is acceptable at this lower bar.

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, front-loaded with the resource scope and followed by the operationally relevant auth note. No filler sentences and nothing redundant with the schema.

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?

With an output schema present, return values need not be explained, and the description covers the content domain and the auth model. The only mild gap is that it never mentions the optional 'os' filter at the top level, though the schema covers it fully.

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?

Schema description coverage is 100% and the single 'os' parameter is fully documented in-schema with an example value and its filtering effect. The description adds no parameter meaning beyond that, so the baseline 3 is appropriate.

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 names a specific resource set (Linux distributions, architectures, Python versions for es-python), so an agent knows exactly what data comes back. The verb is implicit (it is a lookup/listing tool) and there is no sibling differentiation, but no sibling overlaps this domain, so differentiation is not needed.

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?

It notes 'needs no API key', which is a useful operational hint, but never states when to call this versus any alternative or what scenario calls for it (e.g. before choosing an install target). The only conditional guidance ('list only the Python versions for it') lives in the schema, not the description.

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