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Simple Memory MCP Server

Simple Memory MCP Server

by AojdevStudio
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

open_nodes

Access specific nodes in the knowledge graph by name to retrieve their stored data.

Instructions

Open specific nodes in the knowledge graph by their names

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "names": "<names>"
    },
    "name": "open_nodes"
  }
}

Input Schema

NameRequiredDescriptionDefault
namesYesAn array of entity names to retrieve

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing behavior. It only says 'open', which implies read-only retrieval, but does not explicitly state that it is non-mutating, what it returns, or how missing names are handled. This leaves significant ambiguity.

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 a single, efficiently worded sentence that directly states the action and resource. It contains no filler or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema and the description does not clarify what 'open' returns (e.g., node attributes, observations, relations). For an agent to invoke the tool and interpret results correctly, this missing information is a notable gap.

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 input schema has 100% coverage, already describing 'names' as 'An array of entity names to retrieve'. The tool description merely restates 'by their names', adding no extra semantic 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.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Open' and identifies the resource 'nodes in the knowledge graph', scoped by 'names', making it clear this is a direct retrieval by exact names. It implicitly differentiates from search_nodes (searching) and read_graph (full graph), but does not explicitly name alternatives.

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?

No guidance is given on when to use this tool versus siblings. The description does not state that it should be used when exact node names are known, nor does it exclude using search_nodes for lookup or read_graph for broader context.

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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