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Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
RECALL_LOG_LEVELNoLogging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)INFO
RECALL_CHROMA_PATHNoChromaDB persistent storage directory~/.recall/chroma_db
RECALL_OLLAMA_HOSTNoOllama server URLhttp://localhost:11434
RECALL_SQLITE_PATHNoSQLite database file path~/.recall/recall.db
RECALL_OLLAMA_MODELNoEmbedding model namemxbai-embed-large
RECALL_OLLAMA_TIMEOUTNoOllama request timeout in seconds30
RECALL_COLLECTION_NAMENoChromaDB collection namememories
RECALL_DEFAULT_NAMESPACENoDefault namespace for memoriesglobal
RECALL_DEFAULT_IMPORTANCENoDefault importance score (0.0-1.0)0.5
RECALL_DEFAULT_TOKEN_BUDGETNoDefault token budget for context4000

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
daemon_status_tool

Check if the recall daemon is running and healthy.

The daemon provides fast (<10ms) memory storage by queueing operations and processing embeddings asynchronously.

Returns: Dictionary with: - running: Boolean indicating if daemon is running - status: Detailed status if running (uptime, queue stats, cache stats) - error: Error message if not running

memory_store_tool

Store a new memory with semantic indexing, deduplication, and automatic relationship inference.

FAST PATH: If daemon is running, queues for async embedding (<10ms response). The daemon handles embedding and storage in the background.

Auto-linking behavior:

  • ALWAYS works using embedding similarity (no LLM required)

  • Creates 'relates_to' edges for memories above similarity_threshold

  • If LLM available, upgrades edge types to supersedes/contradicts/caused_by

  • Set auto_link=False to disable automatic edge creation

Args: content: The memory content text memory_type: Type of memory (preference, decision, pattern, session) namespace: Scope of the memory (default from RECALL_DEFAULT_NAMESPACE config) importance: Importance score from 0.0 to 1.0 (default from RECALL_DEFAULT_IMPORTANCE config) metadata: Optional additional metadata as dict auto_link: If True, automatically create edges to similar memories (default: True) similarity_threshold: Minimum similarity for auto-linking, 0.0-1.0 (default: 0.6) max_auto_links: Maximum auto-created edges per memory (default: 5) use_llm_classification: If True, use LLM to refine edge types (default: True)

Returns: Result dictionary with: - success: Boolean indicating operation success - queued: True if queued via daemon (fast path) - queue_id: Queue ID if queued via daemon - id: Memory ID (if sync path used) - content_hash: Content hash for deduplication (sync path only) - auto_relationships: List of automatically inferred relationships (sync path only) - error: Error message (if failed)

memory_recall_tool

Recall memories using semantic search with optional multi-hop graph expansion.

Performs semantic search using ChromaDB vector similarity, applies filters, and optionally expands results via graph edges using configurable multi-hop traversal.

Args: query: Search query text (will be embedded with mxbai query prefix) n_results: Maximum number of primary results (default: 5) namespace: Filter by namespace (optional, e.g., 'global' or 'project:myapp') memory_type: Filter by memory type (optional, e.g., 'preference', 'decision') min_importance: Minimum importance score filter (0.0 to 1.0, optional) include_related: If True, include related memories via graph edges (default: False) max_depth: Maximum number of hops for graph expansion (default: 1) max_expanded: Maximum number of expanded memories to return (default: 20) decay_factor: Factor by which relevance decays per hop (default: 0.7) include_edge_types: Optional list of edge types to include (None means all). Valid types: relates_to, supersedes, caused_by, contradicts exclude_edge_types: Optional list of edge types to exclude (None means none). Valid types: relates_to, supersedes, caused_by, contradicts

Returns: Dictionary with: - success: Boolean indicating operation success - memories: List of primary memory dicts with id, content, type, etc. - total: Total count of primary memories returned - score: Average similarity score of primary memories (or None) - expanded: List of expanded memory dicts (when include_related=True) with: - id: Memory ID - content: Memory content - type: Memory type - relevance_score: Combined relevance score (0.0 to 1.0) - hop_distance: Number of edges traversed to reach this memory - path: List of edge types in traversal order - explanation: Human-readable relevance explanation

memory_inspect_graph_tool

Inspect the graph structure around a memory node.

Performs read-only breadth-first search from the origin memory, collecting all nodes and edges within max_depth hops. Returns structured data for visualization including Mermaid diagram generation.

Args: memory_id: ID of the memory to start inspection from max_depth: Maximum number of hops to traverse (default: 2) direction: Edge traversal direction - "outgoing", "incoming", or "both" (default: "both") edge_types: Optional list of edge types to include (None means all). Valid types: relates_to, supersedes, caused_by, contradicts include_scores: If True, compute relevance scores for paths (default: True) decay_factor: Factor by which relevance decays per hop (default: 0.7) output_format: Output format - "json" or "mermaid" (default: "json")

Returns: Dictionary with: - success: Boolean indicating operation success - origin_id: The starting memory ID - nodes: List of node dicts with id, content_preview, type, confidence, importance - edges: List of edge dicts with id, source_id, target_id, edge_type, weight - paths: List of path dicts with node_ids, edge_types, total_weight, relevance_score - stats: Dict with node_count, edge_count, max_depth_reached, origin_id - mermaid: Mermaid diagram string (only when output_format='mermaid') - error: Error message (if failed)

memory_relate_tool

Create a relationship between two memories.

Args: source_id: ID of the source memory target_id: ID of the target memory relation: Type of relationship (relates_to, supersedes, caused_by, contradicts) weight: Edge weight (default: 1.0)

Returns: Result dictionary with success status and edge_id

memory_edge_forget_tool

Delete edges (relationships) between memories.

Supports three deletion modes:

  1. Direct ID: Delete a specific edge by its ID

  2. Memory-based: Delete all edges connected to a memory

  3. Pair: Delete edge(s) between two specific memories

Args: edge_id: Specific edge ID to delete (direct deletion mode) memory_id: Memory ID to delete all connected edges (memory-based mode) source_id: Source memory ID for pair deletion mode target_id: Target memory ID for pair deletion mode relation: Filter by relation type (optional). Valid: relates_to, supersedes, caused_by, contradicts direction: For memory_id mode: 'outgoing', 'incoming', or 'both' (default: 'both')

Returns: Result dictionary with: - success: Boolean indicating operation success - deleted_ids: List of edge IDs that were deleted - deleted_count: Number of edges deleted - error: Error message (if failed)

Examples: Delete by edge ID: edge_id=42 Delete all edges for memory: memory_id="mem_123" Delete specific relation: source_id="mem_123", target_id="mem_456", relation="contradicts"

memory_context_tool

Fetch relevant memories and format them for context injection.

Args: query: Optional search query to filter relevant memories project: Project namespace (auto-detected from cwd if not specified) token_budget: Maximum tokens for context (default from RECALL_DEFAULT_TOKEN_BUDGET config)

Returns: Dictionary with success status and formatted markdown context

memory_forget_tool

Delete memories by ID or semantic search.

Golden rules (type=golden_rule or confidence >= 0.9) are protected from deletion unless force=True is specified.

Args: memory_id: Specific memory ID to delete (direct deletion mode). query: Search query to find memories to delete (search deletion mode). input: Smart parameter that auto-detects if value is an ID or query. namespace: Filter deletion to specific namespace (optional). n_results: Number of search results to delete in query mode (default: 5). confirm: If True, proceed with deletion (default: True). force: If True, allow deletion of golden rules (default: False).

Returns: Result dictionary with success status, deleted_ids, and deleted_count.

Note: If both memory_id and query are None but input is provided, the function auto-detects whether input is a memory ID or search query.

file_activity_add

Record a file activity event.

Used by PostToolUse hooks to track what files have been accessed.

Args: file_path: Path to the file that was accessed action: Type of action (read, write, edit, multiedit) session_id: Optional session ID for grouping activities project_root: Optional project root directory file_type: Optional file type (e.g., 'python', 'typescript') metadata: Optional additional metadata

Returns: Result dictionary with success status and activity_id

file_activity_recent

Get recently accessed files with aggregated activity.

Args: project_root: Filter by project root (optional) limit: Maximum number of files to return (default: 20) days: Look back this many days (default: 14)

Returns: Dictionary with success status and list of recent files

memory_validate_tool

Validate a memory and adjust its confidence score.

Adjusts confidence based on whether the memory was useful:

  • Success: confidence += adjustment (max 1.0)

  • Failure: confidence -= adjustment * 1.5 (min 0.0)

Automatically promotes to GOLDEN_RULE when confidence reaches 0.9.

Args: memory_id: ID of the memory to validate success: Whether the memory application was successful adjustment: Base confidence adjustment (default: 0.1)

Returns: Result with old/new confidence, promotion status, or error

memory_apply_tool

Record that a memory is being applied.

Creates a validation event to track when a memory is used in practice. This starts the TRY phase of the validation loop.

Args: memory_id: ID of the memory being applied context: Description of how/where the memory is being applied session_id: Optional session identifier

Returns: Result with event ID or error

memory_outcome_tool

Record the outcome of a memory application and adjust confidence.

Records whether applying a memory succeeded or failed, creating a validation event and adjusting confidence accordingly.

Args: memory_id: ID of the memory that was applied success: Whether the application was successful error_msg: Optional error message if failed session_id: Optional session identifier

Returns: Result with updated confidence and promotion status

memory_detect_contradictions

Detect memories that contradict a given memory.

Uses semantic search to find similar memories, then LLM reasoning to determine if they actually contradict each other.

Args: memory_id: ID of the memory to check for contradictions similarity_threshold: Minimum similarity for considering contradictions (default: 0.7) create_edges: Whether to create CONTRADICTS edges (default: True)

Returns: Result with list of contradicting memory IDs and edges created

memory_check_supersedes

Check if a memory should supersede another based on validation history.

A newer memory supersedes an older one when it consistently succeeds where the older one failed on similar topics.

Args: memory_id: ID of the (potentially newer) memory to check create_edge: Whether to create SUPERSEDES edge (default: True)

Returns: Result with superseded memory ID if applicable

memory_analyze_health

Analyze the health of memories in the system.

Checks for unresolved contradictions, low-confidence memories, and stale memories that haven't been validated recently.

Args: namespace: Limit analysis to specific namespace (optional) include_contradictions: Check for contradictions (default: True) include_low_confidence: Find low-confidence memories (default: True) include_stale: Find stale memories (default: True) stale_days: Days without validation to consider stale (default: 30)

Returns: Dictionary with categorized issues and recommendations

memory_count_tool

Count memories with optional filters.

Provides a quick count of memories in the system, optionally filtered by namespace and/or memory type.

Args: namespace: Filter by namespace (optional, e.g., 'global' or 'project:myapp') memory_type: Filter by type (optional, e.g., 'preference', 'decision', 'golden_rule')

Returns: Dictionary with count and applied filters

memory_list_tool

List memories with filtering and pagination.

Browse memories in the system with optional filters and pagination. Useful for auditing, exploring, or debugging memory contents.

Args: namespace: Filter by namespace (optional) memory_type: Filter by type (optional) limit: Maximum number of results (default: 100, max: 1000) offset: Number of results to skip for pagination (default: 0) order_by: Field to sort by (default: 'created_at', options: 'created_at', 'accessed_at', 'importance', 'confidence') descending: Sort in descending order (default: True)

Returns: Dictionary with list of memories and pagination info

validation_history_tool

Get validation event history for a memory.

Shows the history of validation events (applied, succeeded, failed) for a specific memory. Useful for understanding why a memory has its current confidence score.

Args: memory_id: ID of the memory to get history for event_type: Filter by event type (optional: 'applied', 'succeeded', 'failed') limit: Maximum number of events to return (default: 50)

Returns: Dictionary with validation events and summary statistics

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

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