Superlocalmemoryv2 MCP Server

Local-first agent memory with MCP and an agent-native CLI. Documented clients include Claude Code, Cursor, and Windsurf.

Remote serverstreamable-httpPython

What is the Superlocalmemoryv2 MCP server?

Superlocalmemoryv2 MCP server is a hosted integration for AI assistants that speak the Model Context Protocol. Local-first agent memory with MCP and an agent-native CLI. Documented clients include Claude Code, Cursor, and Windsurf.

What you get

  • Temporal depth — — the time-aware retrieval and lifecycle described above
  • Governance & EU compliance — — team roles, workspace isolation, a login gate, multi-scope memory, GDPR access/erasure/portability rights, a hash-chained audit trail, and per-mode EU AI Act self-assessment
  • Framework adapters — — drop-in, engine-backed memory for nine agent frameworks
  • Bounded loops — — gate-verified agent loops where an independent check, not the agent's own claim, decides when a task is done
  • Stronger cache and compression — — exact-match caching with tagged invalidation plus opt-in reversible compression, across proxy, MCP, and skill surfaces
  • Stability — — a long defect-and-audit sweep across ingestion, retrieval, mesh, and the dashboard hardens the everyday path

Setting it up

Being a remote server, there is no local install. You register the endpoint with your client, authorise it once, and the tools appear.

What the assistant can call

Once Superlocalmemoryv2 is connected, these are the calls the assistant has available:

  • Stability — a long defect-and-audit sweep across ingestion, retrieval, mesh, and the dashboard hardens the everyday path
  • Agent — controlled caching of repeated file reads → MCP tools (B)
  • Capability — What ships today
  • Ingestion — Durable raw-to-complete operation state, fact extraction, entity resolution, graph/temporal/provenance derivations, and replay-safe identity
  • Optimize — Exact cache, tagged invalidation, safe compression, opt-in aggressive prose compression, CCR originals, proxy/MCP/skill surfaces
  • Mesh — Authenticated peer messages, inbox/outbox, locks, offline queue, optional discovery and mesh MCP tools
  • Integrations — CLI, Python SDK, MCP HTTP/stdio, Claude plugin, Codex add-on, supported IDE configurations, Gmail/Calendar/transcript adapters
  • Workspace — Use it to inspect or control
  • Brain — consolidation, behavioral patterns, outcomes/rewards, learning state and soft prompts
  • Operations — ingestion-operation state, traces, maintenance and lifecycle work
  • Surface — How you use it
  • Memory — Current recall has five candidate producers—dense semantic, BM25 lexical, temporal, Hopfield associative, and spreading activation—followed by

Configuration and credentials

You will need 2 environment variables: SLM_AGENT_ID, ANTHROPIC_BASE_URL. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

Before you rely on it

  • Your data travels to the provider's service, so the usual questions apply about what you send and what they retain.
  • With 12 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch Superlocalmemoryv2.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the superlocalmemoryv2 mcp server does with a few real requests.

Choosing this one

This sits in the knowledge and memory group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Superlocalmemoryv2's toolset — Stability, Agent, Capability and 9 more — is a fair guide to whether it matches your workflow. It is maintained by varun369; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against Superlocalmemoryv2's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Available tools

ToolWhat it does
Stabilitya long defect-and-audit sweep across ingestion, retrieval, mesh, and the dashboard hardens the everyday path.
Agentcontrolled caching of repeated file reads → **MCP tools (B)**
CapabilityWhat ships today
IngestionDurable raw-to-complete operation state, fact extraction, entity resolution, graph/temporal/provenance derivations, and replay-safe identity
OptimizeExact cache, tagged invalidation, safe compression, opt-in aggressive prose compression, CCR originals, proxy/MCP/skill surfaces
MeshAuthenticated peer messages, inbox/outbox, locks, offline queue, optional discovery and mesh MCP tools
IntegrationsCLI, Python SDK, MCP HTTP/stdio, Claude plugin, Codex add-on, supported IDE configurations, Gmail/Calendar/transcript adapters
WorkspaceUse it to inspect or control
Brainconsolidation, behavioral patterns, outcomes/rewards, learning state and soft prompts
Operationsingestion-operation state, traces, maintenance and lifecycle work
SurfaceHow you use it
MemoryCurrent recall has five candidate producers—dense semantic, BM25 lexical, temporal, Hopfield associative, and spreading activation—followed by fusion, optional reranking, and entity-graph score enhancement. The entity gr

How to install the Superlocalmemoryv2 MCP server

{
  "mcpServers": {
    "superlocalmemoryv2": {
      "command": "npx",
      "args": ["-y", "superlocalmemory"],
      "env": {
        "SLM_AGENT_ID": "your-value",
        "ANTHROPIC_BASE_URL": "your-value"
      }
    }
  }
}

Add to claude_desktop_config.json, then restart Claude Desktop.

Configuration

VariableDescriptionRequired
SLM_AGENT_IDConfiguration value read at startup.Optional
ANTHROPIC_BASE_URLEndpoint or connection string the server talks to.Yes

Example prompts to try

  • Use Superlocalmemoryv2 to Stability.
  • Use Superlocalmemoryv2 to Agent.
  • Use Superlocalmemoryv2 to Capability.

Frequently asked questions

It connects Superlocalmemoryv2 to MCP-compatible AI assistants such as Claude and Cursor, exposing 12 tools (Stability, Agent, Capability, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Superlocalmemoryv2 directly.