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Enrique-S-J

sysops-mcp

by Enrique-S-J

check_port

Read-onlyIdempotent

Test whether a TCP port accepts connections to verify a service is listening, returning open, refused, timeout, or DNS failure status.

Instructions

Test whether a TCP port is accepting connections.

Performs a TCP connect to host:port with a timeout. Useful for verifying a service is listening ("is Postgres up on 5432?") before deeper diagnosis.

Returns: str: One-line result: open, closed/refused, timed out, or DNS resolution failure, with latency when the port is open.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hostNoHostname or IP to check (e.g. '127.0.0.1', 'db.internal').127.0.0.1
portYesTCP port number to test (e.g. 22, 443, 5432).
timeout_secondsNoConnection timeout in seconds.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses the actual mechanism (TCP connect with a timeout), the possible outcomes (open, closed/refused, timed out, DNS failure), and that latency is included when open. This gives the agent an accurate mental model of tool behavior without needing to call it speculatively.

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 compact and front-loaded: purpose first, then mechanism/use case, then return format. Every sentence contributes useful information without redundancy. The return contract is clearly specified in a structured way.

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 the simple three-parameter schema, rich annotations, and output-schema signal, the description covers everything an agent needs: what it does, how it behaves, and what it returns. No critical gap remains, and the tool is simple enough that additional detail would be noise.

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 every parameter (host, port, timeout_seconds) is already well documented with defaults, ranges, and examples. The tool description mentions a timeout generally but adds no parameter-level detail beyond the schema, so the baseline 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 opens with a specific verb and resource: 'Test whether a TCP port is accepting connections.' It clearly distinguishes this tool from the sibling system-monitoring tools (CPU, memory, disk, processes) by focusing on network reachability of a specific port. The example 'is Postgres up on 5432?' makes the purpose immediately concrete.

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 provides clear usage context: 'Useful for verifying a service is listening... before deeper diagnosis.' This tells an agent when to reach for the tool. It does not explicitly name alternatives or list when-not-to-use scenarios, so it stops short of a 5.

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

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