mcp-memory-graph

memory_attribution

Read-only

Aggregates top-level memories per agent, distinguishing agent from human author, with optional scope and namespace filters.

Instructions

Multi-agent / team attribution rollup. Returns how many currently-valid top-level memories each agent (agent_id, set at store time) wrote — { by_agent, by_author, total } — distinct from author (the human/source). Memories stored without an agent_id are bucketed under "unattributed". Optional scope/namespace filters scope the rollup.

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": "memory_attribution"
  }
}

Input Schema

Name	Required	Description	Default
`scope`	No	Memory scope for isolation
`namespace`	No	Namespace within scope (e.g., project name, team name)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.6.4Jun 17, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds valuable behavioral context: it only counts 'currently-valid top-level memories', handles unattributed memories by bucketing them, and describes the return structure in detail, which goes beyond the annotations.

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, front-loading key functionality and structure. Every sentence adds essential information with no redundancy or fluff.

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

Completeness5/5

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

Given the tool has only two optional parameters and no output schema, the description fully explains the return structure and filtering. It covers all necessary aspects for an agent to correctly use the 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%, with each parameter described (scope: 'Memory scope for isolation', namespace: 'Namespace within scope'). The description mentions optional filters but adds no new meaning beyond the schema, so baseline 3 is appropriate.

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 tool returns an attribution rollup of top-level memories by agent, with specific fields (by_agent, by_author, total). It distinguishes itself by noting the difference between agent and author, and mentions unattributed memories, which sets it apart from sibling tools like memory_stats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for multi-agent/team attribution and includes optional filters, but does not explicitly state when to avoid this tool or mention alternatives. It provides clear context but lacks explicit guidance on when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server