Store or update an entity by (category, key). Idempotent — call as often as you want, same key returns an update. Optional always_on=true injects entity into every mimir_context. Optional certainty (0.0-1.0) is used by mimir_conflicts for typed-entity conflict detection. Use this for saving facts, decisions, architecture notes, and conventions. When encryption is enabled, body_json is encrypted at rest with AES-256-GCM.

Search entities with FTS5 keyword search. Words are OR'd together. Returns entities sorted by relevance with expanded content/summary fields at top level. Use this to find previously stored facts, decisions, or architecture notes. When encryption is enabled, body_json is decrypted transparently.

Ask a natural language question and get a grounded answer from stored memories via RAG. Internally recalls top-k entities, assembles context, and queries the configured LLM (Ollama) for an answer with cited sources. Requires --llm-endpoint to be set.

Get an entity by ID with its full body_json content. Use after mimir_recall with preview_cap to read the complete body of a truncated result. The drill-down footer embedded in preview-capped results references this tool with the entity ID to use.

Bi-temporal time-travel: return the version of a fact (category + key) that Mimir believed at a given past instant. When a fact is overwritten, the prior version is kept in history; this returns whichever version was live at as_of_unix_ms. Use to answer 'what did we believe about X back then?' or to audit how a fact changed. Returns found=false if the fact had not been recorded yet at that time.

Soft-delete an entity by setting archived=1. The entity is hidden from queries but recoverable. Use this to clean up stale or incorrect facts without permanent data loss.

Sync external data connectors (GitHub issues, file watcher) into Mimir. Call with no arguments to run all enabled connectors, or specify a connector name to run only that one. Use dry_run=true to preview without storing.

Ingest a document file into memory by extracting its text LOCALLY (no cloud, no network). Plaintext/markdown/structured-text work in any build; DOCX and PDF require a binary built with --features multimodal (otherwise a clear error is returned). The extracted text is stored as a normal entity (recallable via mimir_recall). category defaults to 'document', key defaults to the file name.

Generate and store dense vector embeddings for entities via Ollama /api/embed. Supports single entity (category+key) or batch mode (batch_category). Requires --llm-endpoint to be set.

Bulk archive entities by category, decay threshold, or age. Use dry_run=true to preview without archiving. Useful for cleaning stale or low-quality memories.

Create a relationship link from one entity to another. Builds a knowledge graph that mimir_traverse can walk. Use 'depends_on', 'implements', 'extends', 'references', or custom relationships.

Remove a relationship link from one entity to another. Use this to correct outdated or incorrect links in the knowledge graph.

Append a structured decision/observation log entry. Uses evaluated/acted/forward pattern: what was considered, what was done, and what happens next. Essential for audit trails and timeline reconstruction.

Query journal events by time range with optional filters for event type, category, or entity. Use this to reconstruct the decision history and understand what happened when.

Set a key-value state entry with optional TTL for auto-expiration. Use this for session state, temporary flags, or configuration values that should expire after a set time.

Get a state value by key. Returns null if the key has expired or doesn't exist. Use this instead of mimir_recall for transient session state that doesn't need FTS5 search.

Delete a state entry by key. Permanent removal — unlike mimir_forget which is a soft-delete. Use this to clean up expired or unused state entries.

List all state keys, optionally filtered by a key prefix. Use this to discover what state entries exist without knowing exact keys ahead of time.

Check whether the Mimir server and its SQLite database are healthy. Returns a simple healthy/unhealthy status. Use this for health checks and monitoring, not for detailed stats (use mimir_stats).

Return comprehensive database statistics: entity counts by category, type, and decay layer; journal event count; state entry count; database file size; and date range of stored data.

Archive entities whose decay score has fallen below a threshold. Supports dry-run mode to preview without making changes. Run periodically or threshold-triggered to keep the database focused on active, high-value memories.

Permanently delete all archived entities and run VACUUM to reclaim disk space. This is the only operation that actually removes entities — prune/forget only soft-archive. Archived entities are DELETED and NOT RECOVERABLE. Supports dry_run=true to preview first.

Migrate a v0.1.x Mimir database to the current v0.5.0 schema. Reads the old database, converts memories to the entity model, and merges into the current database. Use this once per legacy database during upgrade.

Return a pre-formatted markdown context block of the most important entities for session injection. The downstream system (Perseus) uses this to pre-load AI agent context with relevant memories before work begins.

Extract structured knowledge — facts, preferences, temporal events, episodes — from raw text or a stored entity, using a fully local, deterministic rule-based extractor (no cloud LLM, no embedding/API call, no network). Read-only: never writes to the store. Provide text, or category + key to extract from a stored entity.

Walk the entity link graph starting from a given entity up to a configurable depth. Returns a chain of linked entities — useful for exploring dependencies, decision trees, and relationship graphs built via mimir_link.

Assign a quality score (0.0–1.0) to an entity. Verified entities with high scores resist decay and rank higher in recall results. Use this to mark entities as accurate, verified, or deprecated.

Detect conflicting entities in the same category — pairs with low trigram similarity in their body_json. Flags potential contradictions, duplicate-but-divergent entries, and stale-overwritten facts. Read-only by default. Opt in with resolve=true to actively invalidate the lower-certainty side of clear conflicts (superseding it into history, reversible + time-travelable via mimir_as_of); that path defaults to dry_run=true so you preview first, and never resolves pairs whose certainties are within certainty_margin.

Export all non-archived entities to .md files with YAML frontmatter in a vault directory. Files are human-readable, git-trackable, and Obsidian-compatible. Use this for backup, transfer between workspaces, or offline review.

Import .md files from a vault directory into the database. Reads YAML frontmatter for metadata and markdown body for content. Idempotent — re-running on the same vault won't duplicate entities. Pair with mimir_vault_export for transfer.

Recalculate Ebbinghaus decay scores for all entities based on time since last access. Auto-archives entities that have fully decayed (score < 0.05). Run periodically to keep memory fresh — decayed entities surface less often in recall results.

Rebuild the FTS5 search index from the entities table. Repairs index drift — e.g. after a direct SQLite write, an interrupted archive, or a legacy database written before the atomic prune/forget fixes — so archived entities stop surfacing in recall/search. Returns the number of entities reindexed.

List all distinct entity categories present in the database. Use this to discover what knowledge domains exist before querying with mimir_recall or mimir_context.

Search entities whose recall_when triggers match a given context. Use this for proactive just-in-time memory injection — before writing code, before plans, at session start. Pass the current task description as context and get back memories that declared they should be recalled in similar situations.

Run an autonomous coherence grooming pass over the memory. Promotes buffer entities to working layer, applies decay, auto-links related entities, and archives stale ones below the decay threshold. Use dry_run=true to preview without making changes.

Share an entity to another workspace. Copies the entity (by category + key) from its current workspace into the target workspace, preserving content and metadata while generating a new ID. The original entity is unchanged. Use this for controlled cross-workspace knowledge transfer.

Federate entities from one workspace to another. Exports entities scoped to from_workspace, remaps their workspace_hash to to_workspace, and imports them — effectively copying or moving knowledge between workspaces. Use this for cross-agent or cross-project knowledge sharing without manual file transfer.

Capture a user correction to the agent. Stores what went wrong, what the user said, and the lesson learned — as both a 'correction' entity and a journal entry. Use this every time the user corrects your approach. Enables the self-improving feedback loop: the agent learns from mistakes across sessions.

LLM-driven session synthesis. Reviews a session transcript and extracts structured lessons: what worked (success), what failed (failure), what was corrected (correction), what was abandoned (dead_end), and key decisions made (decision). Each lesson becomes an entity linked to a synthesis journal entry. Requires --llm-endpoint to be configured. This is the Perplexity-Brain-style overnight synthesis loop for agent self-improvement.

Record a performance benchmark data point. Tracks task metrics (turns taken, tokens used, success) alongside whether memory recall was used — enabling measurement of Mimir's impact on agent performance. Aggregate with mimir_recall to analyze trends.

Run a full atomic grooming pass: cohere (promote, link, archive), then decay (recalculate Ebbinghaus decay), then compact (archive below threshold). Returns a summary report. Use dry_run=true to preview without changes.

Create a 'supersedes' relationship from a new fact to an old one, setting the old entity's status to 'deprecated'. Use this when a newer entity makes an older one obsolete.

Database maintenance operations: deduplicate entities with identical (category, key), detect orphan journal entries and links, vacuum (reclaim disk space), reindex FTS5. Set dry_run=true to preview. Use 'all' to run everything.