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Knowledge Graph Memory Server

Knowledge Graph Memory Server

by modelcontextprotocol
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TypeScript
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Read Graph

read_graph
Read-onlyIdempotent

Retrieve the complete knowledge graph to let Claude recall stored user information and relationships across chats. Use it to load persistent memory for context-aware responses.

Instructions

Read the entire knowledge graph

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
entitiesYes
relationsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedOutput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Changed2 schema fields changed
    • addedInput schema / $schema
      Added value: +"http://json-schema.org/draft-07/schema#"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "entities": {
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "entityType": {
+            "description": "The type of the entity",
+            "type": "string"
+          },
+          "name": {
+            "description": "The name of the entity",
+            "type": "string"
+          },
+          "observations": {
+            "description": "An array of observation contents associated with the entity",
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          }
+        },
+        "required": [
+          "name",
+          "entityType",
+          "observations"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "relations": {
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "from": {
+            "description": "The name of the entity where the relation starts",
+            "type": "string"
+          },
+          "relationType": {
+            "description": "The type of the relation",
+            "type": "string"
+          },
+          "to": {
+            "description": "The name of the entity where the relation ends",
+            "type": "string"
+          }
+        },
+        "required": [
+          "from",
+          "to",
+          "relationType"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "entities",
+    "relations"
+  ],
+  "type": "object"
+}
  3. First observedv1.0.0

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered by structured data. The description's contribution is the 'entire' scope, which warns that the whole graph is returned (potentially large), but it says nothing about size, performance, or pagination.

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?

A single five-word sentence that front-loads the verb and scope with zero filler. Nothing could be removed without losing meaning.

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 no-parameter, read-only tool with an output schema (so return values need not be described) and full annotation coverage, the description is nearly sufficient. The only missing piece is a note on expected payload size or when to prefer a scoped sibling.

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?

The tool takes zero parameters, so the baseline is 4. There is nothing for the description to disambiguate, and it correctly avoids inventing parameters.

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?

States a specific verb (Read) and resource (knowledge graph) with an explicit scope qualifier (entire), so the agent knows this is a full-graph fetch rather than a filtered one. It does not name search_nodes or open_nodes, but 'entire' implicitly distinguishes it from those subset readers.

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?

Usage is only implied: 'entire' hints that this is for whole-graph retrieval versus the targeted sibling tools (search_nodes, open_nodes), but there is no explicit when-to-use or when-not-to-use statement. The agent must infer the tradeoff itself.

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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