Velixar Cognitive Memory

Query recent tool calls made by THIS MCP session (in-process diagnostics, volatile, completed calls only). For the durable, hash-chained provenance trail pass durable:true — that queries the backend audit chain.

Store multiple memories in one call. Returns per-item status. Use for bulk imports or multi-fact storage. Max 20 items per call.

List all available Velixar tools, resources, prompts, and features. Use to discover what cognitive capabilities are currently enabled.

Merge related episodic memories into a single semantic memory. Preserves originals as provenance. Use when multiple episodic memories cover the same topic and should be unified. Provide memory IDs to consolidate, or a topic to auto-find candidates. Set preview=true to see what would be merged without executing.

Synthesize the best working brief for the current workspace. Recommended first tool for any new task. Returns summary, relevant facts, open issues, contradiction flags, and pattern hints.

Surface conflicting beliefs, preferences, or facts. Supports resolve action to mark contradictions as resolved. Returns pairs of contradicting statements with severity and linked memory IDs.

Check how well retrieved memories cover a topic. Returns coverage ratio, gaps, and suggested follow-up queries. Anti-hallucination guardrail — use before synthesizing an answer to verify completeness.

Get debug information about the current Velixar MCP server state. Returns workspace config, cache state, API timings, retry counts, circuit breaker state.

Delete or archive memories. Use archive: true for soft-delete (recoverable).

Find which data sources contain information about a topic via knowledge graph. Returns source names, tables, and related insights.

Extract durable memories from session content. Use at natural memory-worthy breakpoints: task complete, decision made, bug solved, preference clarified. Detects duplicates (skips near-identical content) and flags active contradictions. Use preview: true to see extractions without storing.

Export memories as structured data (JSON or Markdown). Supports filtering by tags, tier, date range, and search query.

Fuzzy entity search by name or type. Use to find entities without knowing exact names.

KG overview — entity count, relationship count, top entity types. Workspace-scoped.

Walk relationships from an entity — "what connects to X?" Supports fuzzy entity matching, relationship and entity type filtering.

Check Velixar backend connectivity and health. Returns connection state, workspace, and latency.

User profile — preferences, expertise, communication style, recurring goals, stable constraints. Supports get (default), store, update, delete, list, and history actions. Workspace-scoped.

Bulk import memories from structured data (JSON or Markdown). Max 50 items per call. Supports conflict detection: skip duplicates, overwrite, or merge.

Deep inspection of a specific memory — raw content, provenance, relations, chain links.

Trace the DERIVATION lineage of a memory — the knowledge-building graph, NOT similarity. Every edge was declared at store time via source_ids ("this memory was reasoned/built FROM those"). This answers "what understanding did this come from, and what was built on it" — fundamentally different from velixar_search_neighborhood, which finds memories that merely resemble one another in vector space. Upstream = ancestors (what it was built on); downstream = descendants (what was built on it). A memory with no ancestors is an origin (learned fresh). Returns nodes (each with hop distance and is_origin) and directed child→parent edges.

List recent memories with pagination. Returns full metadata including IDs, tags, and timestamps. Supports filtering by tags, date range, tier, and memory type.

List all connected data sources for the current customer. Supports filtering by type and status.

Search from multiple angles simultaneously with deduplication and temporal awareness. Returns merged results by default. Set merge: false for per-query results (replaces velixar_batch_search).

Surface recurring problem/solution motifs from memory. Omit topic to return all detected patterns. Supports dismiss action.

Assemble a token-budgeted, task-aware context package with explicit gap declaration. Runs multi-angle search, coverage check, and temporal analysis internally.

Query a live data source through Marco Polo. Returns real-time data (ground truth). Natural language query is translated to SQL/API call. Always tag results as [LIVE DATA].

Expand a section, fill a gap, or add a topic to an existing context package. Accepts a single action or an array of actions for batch refinement.

Update tags on one or more memories. Use for organizing, correcting, or enriching memory metadata. Supports add, remove, or replace operations.

Search stored memories by semantic similarity. Returns ranked results with relevance scores. Supports filtering by tags, date range, tier, and memory type.

Find memories near a known memory in vector space. Classifies results as forward (newer chain links), backward (older), or lateral (related but independent).

Get or set the security scanning mode for memory content. Modes: "permissive" (default), "strict" (PII redaction), "off" (no scanning).

Recall memories from a previous session by session ID, date, or topic. Use when resuming work to restore prior context. Supports chunk_id for drill-down into specific time segments (from session_resume manifest). Use order="chronological" for full narrative reconstruction (oldest-first).

Reconstruct full session context in a single call — the recommended way to resume work. Returns narrative summary, key decisions, open threads, and last state.

Save a session summary for later recall. Auto-generates session_id if not provided. Returns the session_id for later recall.

Store a memory for later retrieval. Use for important facts, decisions, user preferences, project context, or anything worth remembering long-term. Memories are workspace-scoped and persist across sessions. Long content is automatically chunked; max 50,000 characters (larger is rejected with a 400 before embedding — split it or chunk client-side). DEDUP (before you call): exact byte-identical duplicates are always blocked server-side. If this content may overlap semantically with existing memories, either velixar_search first or pass check_duplicate:true to run a near-duplicate check.

Show how a topic, entity, or belief evolved over time. Supports date range filtering and summary mode for long histories.

Update an existing memory's content or tags.

Upload a file into Velixar memory with full source provenance. Supports PDF, Markdown, text, CSV, JSON, DOCX, and code files. Parsed, chunked, and tagged with source metadata.