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SharedMemory MCP Server

SharedMemory MCP Server

Official
by sharedmemoryai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

search_entities

Search for entities in the knowledge graph by matching names to find people, projects, concepts, and more.

Instructions

Search for entities in the knowledge graph by name. Useful for finding people, projects, concepts, etc.

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": {
      "query": "<query>"
    },
    "name": "search_entities"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesSearch term (matched against entity names)
volume_idNoVolume ID. Uses default if not set.
limitNoMax results. Default: 20

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.8.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It implies a read-only search operation, but does not explicitly state that it is non-destructive or any other behavioral traits. However, for a search tool, this is acceptable.

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, well-structured sentence that covers purpose and use cases 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?

For a simple search tool with three parameters and no output schema, the description is adequate. It explains what the tool does and when to use it, though it could mention the return format or that results are entity identifiers.

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 coverage is 100%, with descriptions for all three parameters. The description adds no additional meaning beyond the schema, providing a baseline score of 3.

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 it searches for entities in the knowledge graph by name, and gives examples (people, projects, concepts). This differentiates it from siblings like get_entity (likely by ID) and query (more general).

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?

The description offers use cases ('useful for finding people, projects, concepts') but does not explicitly state when not to use it or suggest alternatives. For example, it doesn't mention get_entity for when you have an ID.

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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