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sqlite-memory-mcp

sqlite-memory-mcp

by RMANOV
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

create_entities

Create new entities in the knowledge graph by specifying name, type, and observations. Duplicates are automatically ignored.

Instructions

Create new entities in the knowledge graph.

Each entity dict has: name (str), entityType (str), observations (list[str]). Optional: project (str). Duplicates are silently ignored.

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": {
      "entities": "<entities>"
    },
    "name": "create_entities"
  }
}

Input Schema

NameRequiredDescriptionDefault
entitiesYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.12.5

TDQS

A3.8/5.0
Behavior3/5

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

No annotations provided, so description carries burden. It discloses that duplicates are silently ignored, but lacks details on validation, errors, or side effects.

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?

Three concise sentences: purpose, parameter structure, and behavioral note. Efficiently front-loaded with no wasted words.

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?

Adequately covers purpose, input structure, and a key behavior. Output schema exists, so return values are covered there. Missing information on error handling or constraints.

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

Parameters4/5

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

Schema description coverage is 0%, but the description specifies the structure of each entity dict (name, entityType, observations, optional project), adding meaning beyond the schema's generic object type.

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 'Create new entities in the knowledge graph', using a specific verb and resource. It distinguishes from sibling tools like add_observations and create_relations.

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 on when to use this tool versus alternatives, no exclusion criteria or prerequisites mentioned. The description only implies usage for creating entities.

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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