memory-bank-mcp

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graph_upsert_entity

Upsert a knowledge graph entity: create or update by name and type, with custom attributes, to maintain persistent memory of people, projects, or concepts.

Instructions

Create or update an entity in the knowledge graph. If an entity with the same name exists, it will be updated.

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": {
      "name": "<name>",
      "entityType": "<entityType>"
    },
    "name": "graph_upsert_entity"
  }
}

Input Schema

Name	Required	Description
`storeId`	No	Optional store ID to target a specific registered store instead of the active one
`name`	Yes	Entity name (human-readable identifier)
`entityType`	Yes	Type of entity (e.g., "person", "project", "concept")
`attrs`	No	Optional key-value attributes for the entity

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.3.0Apr 30, 2026

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations, the description must disclose behavioral traits. It explains the upsert semantics (update if name exists), which is the primary behavior. However, it does not mention whether attributes are merged or replaced, what happens on failure, or any side effects. The description provides basic transparency but lacks depth for a mutation tool.

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 extremely concise—two short sentences that front-load the core action. Every word adds value, with no repetition or filler. This is an ideal length for quick comprehension.

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?

Given the absence of annotations and output schema, the description lacks important context. It does not explain return values, attribute merging behavior, or what 'update' entails (e.g., partial vs full replacement). For a tool that modifies a knowledge graph, more detail is needed to ensure correct usage.

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?

Input schema has 100% coverage with descriptions for all four parameters. The description adds no additional meaning beyond the schema; it only restates the overall behavior. Baseline 3 is appropriate since the schema already handles parameter documentation sufficiently.

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 clearly states the tool creates or updates an entity, using the specific verb 'upsert' and resource 'entity'. It mentions the key behavior of updating an existing entity with the same name. However, it does not explicitly differentiate from sibling tools like graph_add_observation or graph_link_entities, which handle related but distinct actions.

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 indicates when to use the tool (to create or update an entity by name) but provides no guidance on when not to use it or what alternatives exist among siblings. For example, it does not mention that for pure creation without overwriting, users might need to check existence first. This omission leaves the agent without clear decision boundaries.

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