mcp-memory
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| create_entitiesA | Create or update entities in the knowledge graph. If an entity already exists, merge observations (don't overwrite). Returns the created/updated entities. |
| create_relationsB | Create relations between entities. Both entities must exist. Returns created relations or errors for missing entities. |
| add_observationsC | Add observations to an existing entity. |
| delete_entitiesC | Delete entities and all their relations/observations. |
| delete_observationsC | Delete specific observations from an entity. |
| delete_relationsC | Delete relations between entities. |
| search_nodesB | Search for nodes in the knowledge graph by name, type, or observation content. |
| open_nodesC | Open specific nodes by name. Returns full entity data with observations. |
| read_graphB | Read the entire knowledge graph. Returns all entities with observations and all relations. |
| search_semanticA | Semantic search using vector embeddings. Finds entities most similar to the query. Requires the embedding model to be downloaded (run download_model.py first). |
| migrateA | Migrate data from Anthropic MCP Memory JSONL format to SQLite. This is idempotent — running it multiple times won't duplicate data. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 11 tools
Each tool has a clearly distinct purpose with no significant overlap: entity/relation/observation operations are separated, search functions target different methods, and administrative tools like migrate are unique. The descriptions reinforce distinct boundaries, making misselection unlikely.
All tools follow a consistent verb_noun naming pattern (e.g., add_observations, create_entities, delete_relations), with no deviations in style or convention. This predictability aids agent understanding and tool selection.
With 11 tools, the set is well-scoped for a knowledge graph memory system, covering core operations (CRUD for entities, relations, observations), search capabilities, and administrative functions. Each tool earns its place without bloat.
The tool surface provides complete coverage for the knowledge graph domain: full CRUD for entities, relations, and observations; multiple search methods (by attribute, semantic); graph reading; and data migration. No obvious gaps exist for typical agent workflows.