MCP server intelligence profile

mcp-knowledge-graph MCP Server

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats

Local Onlyshaneholloman
Awaiting current scanNpm · 1.3.2

The selected current version does not yet have completed public verification. Unknown does not mean clean or vulnerable.

1Distribution channel
10Independently observed tools
0Linked remote endpoints
AvailableVersion intelligence

Detailed security scan evidence is not public for this MCP yet. Public identity, registry metadata, and independently observed protocol inventory remain available.

Install and connect

Installation and connection instructions are shown only when supported by retained package, repository, or endpoint evidence.

Install mcp-knowledge-graph from npm

Version 1.3.2 declares 1 executable entrypoint.

npm install --save-exact mcp-knowledge-graph@1.3.2
npx -y -p mcp-knowledge-graph@1.3.2 mcp-knowledge-graph
MCP client configuration example
{
  "mcpServers": {
    "mcp-knowledge-graph": {
      "command": "npx",
      "args": [
        "-y",
        "-p",
        "mcp-knowledge-graph@1.3.2",
        "mcp-knowledge-graph"
      ]
    }
  }
}

Identity

Canonical slugmcp-knowledge-graph-e3ab5ab2DeploymentLocal Only
Canonical packagenpm:mcp-knowledge-graphRepositoryshaneholloman/mcp-knowledge-graph
First publishedLatest release
Last security verificationClassification confidence90%
PublicationDraftOfficial distributionNot verified

Distributions

ChannelIdentifierCurrent versionVersionsSource
npmmcp-knowledge-graph1.3.210Repository

Current release

PackageVersionPublished / observedInventorySecurity scan
npmmcp-knowledge-graph1.3.2CurrentSep 5, 202610 toolsSucceeded · 0 resources · 0 promptsEvidence restricted
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Current version evidence

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Current protocol inventory

2024-11-05Negotiated protocol
mcp-knowledge-graphServer-reported name
1Capability groups
Aug 17, 2026Observed

Tools 10

ToolCategoryAnnotationsRisk
aim_memory_add_factsAdd new facts to an existing memory. Use this to append information to something already stored. IMPORTANT: Memory must already exist - use aim_memory_store first. Throws error if not found. RETURNS: Array of {entityName, addedObservations} showing what was added (duplicates are ignored). DATABASE: Adds to entities in the specified 'context' database, or master database if not specified. EXAMPLES: - aim_memory_add_facts({observations: [{entityName: "John", contents: ["Lives in Seattle", "Works in tech"]}]}) - aim_memory_add_facts({context: "work", observations: [{entityName: "Q4_Project", contents: ["Behind schedule", "Need more resources"]}]})
Input schema
{
  "type": "object",
  "properties": {
    "context": {
      "type": "string",
      "description": "Optional memory context. Observations will be added to entities in the specified context's knowledge graph."
    },
    "location": {
      "type": "string",
      "enum": [
        "project",
        "global"
      ],
      "description": "Optional storage location override. 'project' forces project-local .aim directory, 'global' forces global directory. If not specified, uses automatic detection."
    },
    "observations": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "entityName": {
            "type": "string",
            "description": "The name of the entity to add the observations to"
          },
          "contents": {
            "type": "array",
            "items": {
              "type": "string"
            },
            "description": "An array of observation contents to add"
          }
        },
        "required": [
          "entityName",
          "contents"
        ]
      }
    }
  },
  "required": [
    "observations"
  ]
}
aim_memory_forgetForget memories. Removes memories and their associated links. DATABASE SELECTION: Entities are deleted from the specified database's knowledge graph. LOCATION OVERRIDE: Use the 'location' parameter to force deletion from 'project' (.aim directory) or 'global' (configured directory). Leave blank for auto-detection. EXAMPLES: - Master database (default): aim_memory_forget({entityNames: ["OldProject"]}) - Work database: aim_memory_forget({context: "work", entityNames: ["CompletedTask", "CancelledMeeting"]}) - Master database in global location: aim_memory_forget({location: "global", entityNames: ["OldProject"]}) - Personal database in project location: aim_memory_forget({context: "personal", location: "project", entityNames: ["ExpiredReminder"]})
Input schema
{
  "type": "object",
  "properties": {
    "context": {
      "type": "string",
      "description": "Optional memory context. Entities will be deleted from the specified context's knowledge graph."
    },
    "location": {
      "type": "string",
      "enum": [
        "project",
        "global"
      ],
      "description": "Optional storage location override. 'project' forces project-local .aim directory, 'global' forces global directory. If not specified, uses automatic detection."
    },
    "entityNames": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "An array of entity names to delete"
    }
  },
  "required": [
    "entityNames"
  ]
}
aim_memory_getRetrieve specific memories by exact name. Use this when you know exactly what you're looking for. VS aim_memory_search: Use aim_memory_get for exact name lookup. Use aim_memory_search for fuzzy matching or when you don't know exact names. RETURNS: Requested entities and relations between them. Non-existent names are silently ignored. FORMAT OPTIONS: - "json" (default): Structured JSON for programmatic use - "pretty": Human-readable text format EXAMPLES: - aim_memory_get({names: ["John", "TechConf2024"]}) - JSON format - aim_memory_get({names: ["Shane"], format: "pretty"}) - Human-readable - aim_memory_get({context: "work", names: ["Q4_Project"], format: "pretty"})
Input schema
{
  "type": "object",
  "properties": {
    "context": {
      "type": "string",
      "description": "Optional memory context. Retrieves entities from the specified context's knowledge graph or master database if not specified."
    },
    "location": {
      "type": "string",
      "enum": [
        "project",
        "global"
      ],
      "description": "Optional storage location override. 'project' for .aim directory, 'global' for configured directory."
    },
    "names": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "An array of entity names to retrieve"
    },
    "format": {
      "type": "string",
      "enum": [
        "json",
        "pretty"
      ],
      "description": "Output format. 'json' (default) for structured data, 'pretty' for human-readable text."
    }
  },
  "required": [
    "names"
  ]
}
aim_memory_linkLink two memories together with a relationship. Use this to connect related information. RELATION STRUCTURE: Each link has 'from' (subject), 'relationType' (verb), and 'to' (object). - Use active voice verbs: "manages", "works_at", "knows", "attended", "created" - Read as: "from relationType to" (e.g., "Alice manages Q4_Project") - Avoid passive: use "manages" not "is_managed_by" IMPORTANT: Both 'from' and 'to' entities must already exist in the same database. RETURNS: Array of created relations (duplicates are ignored). DATABASE: Relations are created in the specified 'context' database, or master database if not specified. EXAMPLES: - aim_memory_link({relations: [{from: "John", to: "TechConf2024", relationType: "attended"}]}) - aim_memory_link({context: "work", relations: [{from: "Alice", to: "Q4_Project", relationType: "manages"}]}) - Multiple: aim_memory_link({relations: [{from: "John", to: "Alice", relationType: "knows"}, {from: "John", to: "Acme_Corp", relationType: "works_at"}]})
Input schema
{
  "type": "object",
  "properties": {
    "context": {
      "type": "string",
      "description": "Optional memory context. Relations will be created in the specified context's knowledge graph."
    },
    "location": {
      "type": "string",
      "enum": [
        "project",
        "global"
      ],
      "description": "Optional storage location override. 'project' forces project-local .aim directory, 'global' forces global directory. If not specified, uses automatic detection."
    },
    "relations": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "from": {
            "type": "string",
            "description": "The name of the entity where the relation starts"
          },
          "to": {
            "type": "string",
            "description": "The name of the entity where the relation ends"
          },
          "relationType": {
            "type": "string",
            "description": "The type of the relation"
          }
        },
        "required": [
          "from",
          "to",
          "relationType"
        ]
      }
    }
  },
  "required": [
    "relations"
  ]
}
aim_memory_list_storesList all available memory databases and show current storage location. DATABASE TYPES: - "default": The master database (memory.jsonl) - used when no context is specified - Named databases: Created via context parameter (e.g., "work" -> memory-work.jsonl) RETURNS: {project_databases: [...], global_databases: [...], current_location: "..."} - project_databases: Databases in .aim directory (if project detected) - global_databases: Databases in global --memory-path directory - current_location: Where operations will default to Use this to discover what databases exist before querying them. EXAMPLES: - aim_memory_list_stores() - Shows all available databases and current storage location
Input schema
{
  "type": "object",
  "properties": {}
}
aim_memory_read_allRead all memories in a database. Returns every stored memory and their links. FORMAT OPTIONS: - "json" (default): Structured JSON for programmatic use - "pretty": Human-readable text format DATABASE: Reads from the specified 'context' database, or master database if not specified. EXAMPLES: - aim_memory_read_all({}) - JSON format - aim_memory_read_all({format: "pretty"}) - Human-readable - aim_memory_read_all({context: "work", format: "pretty"}) - Work database, pretty
Input schema
{
  "type": "object",
  "properties": {
    "context": {
      "type": "string",
      "description": "Optional memory context. Reads from the specified context's knowledge graph or master database if not specified."
    },
    "location": {
      "type": "string",
      "enum": [
        "project",
        "global"
      ],
      "description": "Optional storage location override. 'project' for .aim directory, 'global' for configured directory."
    },
    "format": {
      "type": "string",
      "enum": [
        "json",
        "pretty"
      ],
      "description": "Output format. 'json' (default) for structured data, 'pretty' for human-readable text."
    }
  }
}
aim_memory_remove_factsRemove specific facts from a memory. Keeps the memory but removes selected observations. DATABASE SELECTION: Observations are deleted from entities within the specified database's knowledge graph. LOCATION OVERRIDE: Use the 'location' parameter to force deletion from 'project' (.aim directory) or 'global' (configured directory). Leave blank for auto-detection. EXAMPLES: - Master database (default): aim_memory_remove_facts({deletions: [{entityName: "John", observations: ["Outdated info"]}]}) - Work database: aim_memory_remove_facts({context: "work", deletions: [{entityName: "Project", observations: ["Old deadline"]}]}) - Master database in global location: aim_memory_remove_facts({location: "global", deletions: [{entityName: "John", observations: ["Outdated info"]}]}) - Health database in project location: aim_memory_remove_facts({context: "health", location: "project", deletions: [{entityName: "Exercise", observations: ["Injured knee"]}]})
Input schema
{
  "type": "object",
  "properties": {
    "context": {
      "type": "string",
      "description": "Optional memory context. Observations will be deleted from entities in the specified context's knowledge graph."
    },
    "location": {
      "type": "string",
      "enum": [
        "project",
        "global"
      ],
      "description": "Optional storage location override. 'project' forces project-local .aim directory, 'global' forces global directory. If not specified, uses automatic detection."
    },
    "deletions": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "entityName": {
            "type": "string",
            "description": "The name of the entity containing the observations"
          },
          "observations": {
            "type": "array",
            "items": {
              "type": "string"
            },
            "description": "An array of observations to delete"
          }
        },
        "required": [
          "entityName",
          "observations"
        ]
      }
    }
  },
  "required": [
    "deletions"
  ]
}
aim_memory_searchSearch memories by keyword. Use this when you don't know the exact name of what you're looking for. WHAT IT SEARCHES: Matches query (case-insensitive) against: - Memory names (e.g., "John" matches "John_Smith") - Memory types (e.g., "person" matches all person memories) - Facts/observations (e.g., "Seattle" matches memories mentioning Seattle) VS aim_memory_get: Use aim_memory_search for fuzzy matching. Use aim_memory_get when you know exact names. FORMAT OPTIONS: - "json" (default): Structured JSON for programmatic use - "pretty": Human-readable text format EXAMPLES: - aim_memory_search({query: "John"}) - JSON format - aim_memory_search({query: "project", format: "pretty"}) - Human-readable - aim_memory_search({context: "work", query: "Shane", format: "pretty"})
Input schema
{
  "type": "object",
  "properties": {
    "context": {
      "type": "string",
      "description": "Optional database name. Searches within this database or master database if not specified."
    },
    "location": {
      "type": "string",
      "enum": [
        "project",
        "global"
      ],
      "description": "Optional storage location override. 'project' for .aim directory, 'global' for configured directory."
    },
    "query": {
      "type": "string",
      "description": "Search text to match against entity names, entity types, and observation content (case-insensitive)"
    },
    "format": {
      "type": "string",
      "enum": [
        "json",
        "pretty"
      ],
      "description": "Output format. 'json' (default) for structured data, 'pretty' for human-readable text."
    }
  },
  "required": [
    "query"
  ]
}
aim_memory_storeStore new memories. Use this to remember people, projects, concepts, or any information worth persisting. AIM (AI Memory) provides persistent memory for AI assistants. The 'aim_memory_' prefix groups all memory tools together. WHAT'S STORED: Memories have a name, type (person/project/concept/etc.), and observations (facts about them). DATABASES: Use the 'context' parameter to organize memories into separate graphs: - Leave blank: Uses the master database (default for general information) - Any name: Creates/uses a named database ('work', 'personal', 'health', 'research', etc.) - New databases are created automatically - no setup required - IMPORTANT: Use consistent, simple names - prefer 'work' over 'work-stuff' STORAGE LOCATIONS: Files are stored as JSONL (e.g., memory.jsonl, memory-work.jsonl): - Project-local: .aim directory in project root (auto-detected if exists) - Global: User's configured --memory-path directory - Use 'location' parameter to override: 'project' or 'global' RETURNS: Array of created entities. EXAMPLES: - Master database (default): aim_memory_store({entities: [{name: "John", entityType: "person", observations: ["Met at conference"]}]}) - Work database: aim_memory_store({context: "work", entities: [{name: "Q4_Project", entityType: "project", observations: ["Due December 2024"]}]}) - Master database in global location: aim_memory_store({location: "global", entities: [{name: "John", entityType: "person", observations: ["Met at conference"]}]}) - Work database in project location: aim_memory_store({context: "work", location: "project", entities: [{name: "Q4_Project", entityType: "project", observations: ["Due December 2024"]}]})
Input schema
{
  "type": "object",
  "properties": {
    "context": {
      "type": "string",
      "description": "Optional memory context. Defaults to master database if not specified. Use any descriptive name ('work', 'personal', 'health', 'basket-weaving', etc.) - new contexts created automatically."
    },
    "location": {
      "type": "string",
      "enum": [
        "project",
        "global"
      ],
      "description": "Optional storage location override. 'project' forces project-local .aim directory, 'global' forces global directory. If not specified, uses automatic detection."
    },
    "entities": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {
            "type": "string",
            "description": "The name of the entity"
          },
          "entityType": {
            "type": "string",
            "description": "The type of the entity"
          },
          "observations": {
            "type": "array",
            "items": {
              "type": "string"
            },
            "description": "An array of observation contents associated with the entity"
          }
        },
        "required": [
          "name",
          "entityType",
          "observations"
        ]
      }
    }
  },
  "required": [
    "entities"
  ]
}
aim_memory_unlinkRemove links between memories. Keeps the memories but removes their connections. DATABASE SELECTION: Relations are deleted from the specified database's knowledge graph. LOCATION OVERRIDE: Use the 'location' parameter to force deletion from 'project' (.aim directory) or 'global' (configured directory). Leave blank for auto-detection. EXAMPLES: - Master database (default): aim_memory_unlink({relations: [{from: "John", to: "OldCompany", relationType: "worked_at"}]}) - Work database: aim_memory_unlink({context: "work", relations: [{from: "Alice", to: "CancelledProject", relationType: "manages"}]}) - Master database in global location: aim_memory_unlink({location: "global", relations: [{from: "John", to: "OldCompany", relationType: "worked_at"}]}) - Personal database in project location: aim_memory_unlink({context: "personal", location: "project", relations: [{from: "Me", to: "OldHobby", relationType: "enjoys"}]})
Input schema
{
  "type": "object",
  "properties": {
    "context": {
      "type": "string",
      "description": "Optional memory context. Relations will be deleted from the specified context's knowledge graph."
    },
    "location": {
      "type": "string",
      "enum": [
        "project",
        "global"
      ],
      "description": "Optional storage location override. 'project' forces project-local .aim directory, 'global' forces global directory. If not specified, uses automatic detection."
    },
    "relations": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "from": {
            "type": "string",
            "description": "The name of the entity where the relation starts"
          },
          "to": {
            "type": "string",
            "description": "The name of the entity where the relation ends"
          },
          "relationType": {
            "type": "string",
            "description": "The type of the relation"
          }
        },
        "required": [
          "from",
          "to",
          "relationType"
        ]
      },
      "description": "An array of relations to delete"
    }
  },
  "required": [
    "relations"
  ]
}

Resources 0

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Resource templates 0

  • None observed.

Prompts 0

  • None observed.

Remote endpoints

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mcp-knowledge-graph MCP Server questions

How do I install mcp-knowledge-graph MCP Server?

Install the selected package version with: npm install --save-exact mcp-knowledge-graph@1.3.2

What tools does mcp-knowledge-graph MCP Server provide?

mcp-knowledge-graph MCP Server exposed 10 tools during independent protocol observation, including aim_memory_add_facts, aim_memory_forget, aim_memory_get, aim_memory_link, aim_memory_list_stores, aim_memory_read_all, aim_memory_remove_facts, aim_memory_search, and others.

Is mcp-knowledge-graph MCP Server secure?

The selected current version does not yet have completed public verification. Unknown does not mean clean or vulnerable.

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