sqlite-memory-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| BRIDGE_REPO | No | Path to the bridge git repository. Only needed for bridge/collab flows. | |
| SQLITE_MEMORY_DB | No | Path to the SQLite database file. Defaults to ~/.claude/memory/memory.db. | ~/.claude/memory/memory.db |
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| create_entities | Create new entities in the knowledge graph. Each entity dict has: name (str), entityType (str), observations (list[str]). Optional: project (str). Duplicates are silently ignored. |
| add_observations | Add new observations to existing entities. Each dict has: entityName (str), contents (list[str]). Duplicate observations are silently ignored. |
| create_relations | Create relations between entities in the knowledge graph. Each dict has: from (str), to (str), relationType (str). Duplicate relations are silently ignored. |
| delete_entities | Delete entities and their associated observations and relations (CASCADE). Also cleans up the FTS index. |
| delete_observations | Delete specific observations from entities. Each dict has: entityName (str), observations (list[str]). |
| delete_relations | Delete specific relations from the knowledge graph. Each dict has: from (str), to (str), relationType (str). |
| read_graph | Read the full knowledge graph with pagination. Returns JSON: {entities: [{name, entityType, observations: [...]}], relations: [{from, to, relationType}], total: int, has_more: bool} |
| search_nodes | Search the knowledge graph using hybrid BM25 + semantic search. When sqlite-vec is installed, combines FTS5 keyword matching with vector cosine similarity via Reciprocal Rank Fusion. Falls back to FTS5-only otherwise. Results are re-ranked with 6 contextual signals (recency, project affinity, graph proximity, richness, canonical facts, session). |
| open_nodes | Open specific entities and retrieve their inter-relations. Returns the requested entities with observations and all relations that exist between them. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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