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Varun Pratap Bhardwaj edited this page Jul 16, 2026 · 5 revisions

MCP Tools

SuperLocalMemory exposes profile-selected tools and resources through the Model Context Protocol (MCP). The installed profile registry is the source of truth for names and counts. An MCP-compatible client still decides when to call a tool.

Optimize tools: slm_compress, slm_retrieve, slm_cache_set, slm_cache_get, and slm_optimize_stats provide explicit compression and routed-result caching. They do not intercept the primary conversation turn without a proxy.

V3.1 New: 3 Active Memory tools (session_init, observe, report_feedback) and 1 resource (slm://context) for automatic learning and context injection.

Starting the MCP Server

slm mcp    # Starts stdio transport — your IDE calls this automatically

Your IDE config should look like:

{
  "mcpServers": {
    "superlocalmemory": {
      "command": "slm",
      "args": ["mcp"]
    }
  }
}

Core Tools

Tool Parameters Description
remember content, tags?, project?, importance?, session_id?, agent_id?, scope?, shared_with?, idempotency_key? Submit durable evidence and return an operation receipt
recall query, limit? Retrieve relevant memories
search query, limit? Search across all memories
forget query Delete matching memories
fetch id Get a specific memory by ID
list_recent limit? List recent memories
get_status — System status (mode, DB, count, math health)
health — Math layer health (Fisher, Sheaf, Langevin)
build_graph — Rebuild the knowledge graph
get_attribution memory_id Get provenance chain for a memory
compact_memories — Compress and optimize storage
memory_used — Storage usage statistics
backup_status — Backup and database health
audit_trail limit? Recent operations log

remember returns operation_id, fact_ids, materialization_state, and pending. The default daemon path returns after SQLite relational/FTS is queryable; enrichment continues on the same durable operation. Offline replay preserves the original source and idempotency identity.

recall, search, recall_trace, and session context follow Score Contract v2. relevance_score is query relevance, ranking_score is diagnostic ranking utility, and memory_confidence belongs to the stored assertion. V3.7 declares calibration_status: "uncalibrated" and answer_confidence: null.

Active Memory Tools (V3.1)

Tool Parameters Description
session_init project_path?, query? Auto-recall project context at session start. Returns relevant memories + learning status. Call once at the beginning of every session.
observe content Send conversation content for auto-capture. Detects decisions, bug fixes, and preferences. Stores automatically when confidence > 0.5.
report_feedback fact_id, feedback, query? Report whether a recalled memory was useful. Feedback: "relevant", "irrelevant", or "partial". Trains the adaptive ranker.

Management Tools

Tool Parameters Description
switch_profile name Switch to a different memory profile
set_retention_policy days, categories? Set data retention period
report_outcome memory_id, outcome Report whether a recalled memory was helpful
correct_pattern pattern_id, correction Correct a learned behavioral pattern
get_behavioral_patterns limit? View learned patterns
get_learned_patterns limit? View ML-learned recall patterns

V3 Tools

Tool Parameters Description
recall_trace query Recall with per-channel score breakdown
get_lifecycle_status — Memory lifecycle health (active/warm/cold counts)
consistency_check — Run sheaf consistency verification
set_mode mode Switch operating mode (a/b/c)
get_mode — Current operating mode

Resources

MCP resources provide read-only data streams that IDEs can subscribe to.

Resource URI Description
Memory Stats memory://stats Total memories, storage size, profile count
Recent Memories memory://recent Last 10 memories stored
Active Profile memory://profile Current profile name and settings
System Health memory://health Database status, math layer scores
Knowledge Graph memory://graph Graph summary (nodes, edges, communities)
Learning State memory://learning ML model state and learned patterns

Optimize Tools (v3.6.11)

Proxy-free compression and routed-result caching. The tools are designed to return ok:False with the original content on handled optimization failures; verify the frozen artifact before relying on that as a fault-containment boundary.

Tool Parameters Description
slm_compress content, mode?, reversible?, ttl_seconds? Compress text. mode: normalize (lossless), auto, aggressive. Returns ccr_id when lossy+reversible.
slm_retrieve ccr_id Recover exact original from a lossy compress.
slm_cache_set key, value, ttl_seconds? Cache any string result (file read, bash output, search). Namespaced per agent.
slm_cache_get key Retrieve cached result. Returns hit:True/False.
slm_optimize_stats — Compression + cache statistics for the current session.

Hard constraint: Surfaces B and C cache results you explicitly route through SLM — not the Claude conversation turn. Full-turn caching requires Surface A (proxy).

How MCP Integration Works

  1. Your IDE connects to the SuperLocalMemory MCP server via slm mcp
  2. When you chat with your AI, the IDE calls recall with relevant context
  3. SuperLocalMemory runs the healthy subset of dense semantic, BM25 lexical, temporal, Hopfield associative, and spreading-activation candidate producers, then applies fusion and optional score enhancements
  4. The IDE injects those memories into the AI's context
  5. Your AI responds with knowledge of your past work

Whether this happens automatically depends on the client and its configured instructions or hooks. SLM does not control an IDE's tool-selection policy.

See IDE Setup for per-IDE configuration paths.

Part of Qualixar | Created by Varun Pratap Bhardwaj

SuperLocalMemory V3 — Local-first memory with explicit data-path controls.

Part of Qualixar | Created by Varun Pratap Bhardwaj | GitHub

SuperLocalMemory V3

Getting Started

Reference

Architecture

Enterprise

V2 Documentation

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