Skip to content
memtomem

Overview

What is memtomem-stm?

Section titled “What is memtomem-stm?”

memtomem-stm is a short-term memory (STM) proxy that sits between your AI agent and your existing MCP servers. Without agent-side code changes, it adds response compression, proactive memory injection, and exposed-tool curation to calls routed through the proxy. Token savings depend on response shape, chosen budgets, and workload.

Use It When

Section titled “Use It When”
  • MCP tool responses keep blowing your context window — STM applies content-aware character or token budgets to routed filesystem, GitHub, and other MCP responses.
  • You want memories auto-injected without the agent having to ask — with LTM alone, the agent calls a search tool. With STM in front, eligible routed responses can carry relevant memories without a separate agent query.
  • You want to curate the tool list your agent sees — STM drops unresponsive servers, credential-leaking descriptions, and duplicate-named tools from the advertised list at exposure time.
  • You want to try the proxy without committing — STM imports your existing MCP servers and proxies them in front, and the move is reversible. mms eject restores an imported server to its original host config, returning you to the pre-STM state.

Start in 3 Steps

Section titled “Start in 3 Steps”
Terminal window
uv tool install memtomem-stm                             # 1. install
mms init --demo --client auto                            # 2. create a runnable demo + register a detected client
mms doctor                                               # 3. diagnose the complete setup

mms init --demo creates a deterministic demo upstream. --client auto registers a supported detected host; use mms register --client claude, --client codex, or --client auto later to change registration. The completed call, metrics, prune, and rollback workflow is in Add STM to an MCP Server.

Core Capabilities

Section titled “Core Capabilities”
  • Proactive Surfacing — Every tool call runs candidate memories through 5 relevance checks (context extraction → query suitability → LTM search → score threshold → dedup window) before anything is injected. Surfacing toggles per upstream (mms surfacing <server> on|off), so you can exclude a single server’s responses from surfacing. See Proactive Surfacing.
  • Response Compression — 10 strategies, auto-selected by content type (JSON, Markdown, API docs, free text, …), with query-aware ranking and safer JSON output tiers. See Compression Strategies.
  • Exposed-Tool Curation — STM does not just relay every upstream tool as-is; it curates the advertised tool list at exposure time. Tools from unresponsive servers, descriptions that leak credentials, and duplicate or overflowing names are withheld from the agent. Tune the policy with exposure.profile (strict default / review / explore); stm_proxy_health reports “N discovered / M advertised”.
  • Reversible Import — Imported upstreams record their origin, so mms list distinguishes directly-registered servers from imported ones in an ORIGIN column (* marks a pruned host original). mms eject verifies the restore before it removes the STM entry.

How It Works

Section titled “How It Works”
AI Agent
    ↕  MCP protocol
memtomem-stm (STM Proxy)
    ├── ↕ Surfacing queries → memtomem (LTM)
    └── ↕ Proxied calls → Upstream MCP Servers
                           (filesystem, GitHub, …)

STM runs every MCP tool call through this pipeline:

  1. CLEAN — normalize the request (strip noise, unify format)
  2. COMPRESS — shrink the response (auto-select from 10 strategies)
  3. SURFACE — pull relevant memories from LTM and inject them (5-level gating)

The bundled mms runtime does not write memories back to LTM. Its active response pipeline is CLEAN → COMPRESS → SURFACE, and surfacing reads from LTM over MCP.

Relationship to LTM

Section titled “Relationship to LTM”

STM and LTM are independent packages — no Python dependency between them. They communicate only via MCP protocol, and each can be deployed and upgraded separately.

LTM (memtomem)STM (memtomem-stm)
RolePersistent storage & searchReal-time proxy & compression
Required?Yes (core)Optional
CommunicationDirect MCP serverMCP proxy → queries LTM

Package Info

Section titled “Package Info”
PyPImemtomem-stm
Latest release0.1.41
CLImms
LicenseApache 2.0
GitHubmemtomem/memtomem-stm

Next Steps

Section titled “Next Steps”