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mcp-elasticache-ops

mcp-elasticache-ops

by ritojoao
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Node Cluster Memory

node_cluster_memory
Read-onlyIdempotent

Inspect per-shard primary memory metrics—used, RSS, maxmemory, fragmentation, and evictions—to detect memory skew, shards above 90% maxmemory, and unreachable nodes.

Instructions

node_memory headline for every shard primary: used/RSS/maxmemory, fragmentation, evictions, with findings for memory skew between shards, shards above 90% of maxmemory and unreachable shards.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "node_cluster_memory"
  }
}

Input Schema

NameRequiredDescriptionDefault
max_workersNoConcurrent shard probes
per_node_timeoutNoSeconds to wait per node

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so safety is covered. The description adds genuinely useful behavior: it reports findings for memory skew between shards, shards above 90% of maxmemory, and unreachable shards, which tells the agent that partial node failure surfaces as findings rather than an error. It does not mention how max_workers or per_node_timeout affect the fan-out or whether results are partial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence that front-loads the metric list and appends the derived findings, with no filler. The phrasing 'node_memory headline' is mildly awkward, but every clause carries information about scope or output content.

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?

An output schema exists, so return-value detail is unnecessary, and the two tunables are fully described in the schema. What remains is adequately covered: the fan-out scope, the metrics gathered, and the three finding categories, including the notable unreachable-shard behavior. Only the relationship to the sibling single-node memory tool is left implicit.

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

Parameters5/5

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

Schema description coverage is 100% with only two optional params (max_workers, per_node_timeout), each fully documented in the schema including defaults, bounds and meaning. The description adds nothing parameter-specific, but no compensation is needed, so the baseline applies cleanly.

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?

States a specific verb-less but precise operation: memory headline metrics (used/RSS/maxmemory, fragmentation, evictions) collected for every shard primary. The 'for every shard primary' scope implicitly separates it from the single-node node_memory sibling, though it never names that sibling to make the contrast explicit.

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?

Usage is only implied through the scope phrase 'for every shard primary' – an agent can infer this is the cluster-wide memory rollup rather than a per-node read. There is no explicit when-to-use, when-not-to-use, or named alternative (e.g. node_memory for a single node), leaving the routing decision to inference.

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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