mcp-memory-graph

memory_related

Read-only

Retrieve semantically similar memories by providing a memory ID; uses vector similarity to uncover hidden connections.

Instructions

Find memories semantically related to a given memory ID. Uses vector similarity to discover connections.

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": {
      "id": "<id>"
    },
    "name": "memory_related"
  }
}

Input Schema

Name	Required	Description
`id`	Yes	Memory ID to find related memories for
`limit`	No	Maximum number of related memories to return
`min_similarity`	No	Minimum similarity threshold (0-1)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.6.4Jun 17, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already mark this as read-only (readOnlyHint=true). The description adds behavioral detail by stating it 'uses vector similarity to discover connections', which goes beyond the annotations. No contradictions. For a read-only tool, this is sufficient context.

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 two sentences long, front-loading the core purpose, with no unnecessary words. Every sentence adds value.

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?

The description covers the tool's purpose and method. With 3 parameters fully described in the schema, it is mostly self-contained. However, there is no output schema and the description does not hint at the return format (e.g., list of similar memories with scores), which would improve completeness for a search tool.

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% (all 3 parameters have descriptions). The description does not add significant extra meaning beyond what the schema already provides, so baseline 3 is appropriate. It does provide context that the id parameter is for a memory and that similarity is vector-based, but this is implicit from the tool's purpose.

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 the verb 'find', specifies the resource as 'memories semantically related to a given memory ID', and explains the method 'vector similarity'. This distinguishes it from sibling tools like memory_search (which searches by text query) and memory_get (which retrieves a specific memory).

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 implies the tool's use case (finding related memories by ID) but provides no explicit guidance on when to use it versus alternatives, nor does it mention exclusions or prerequisites. Given many sibling tools, explicit context would improve this dimension.

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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