Environment Variables

Both memtomem (LTM) and memtomem-stm (STM) use pydantic-settings with env_prefix + env_nested_delimiter="__". Nested settings use double underscore — MEMTOMEM_EMBEDDING__PROVIDER, not MEMTOMEM_EMBEDDING_PROVIDER.

Resolution order (highest priority first): CLI flags → environment variables → config file → built-in defaults.

LTM (memtomem) — prefix `MEMTOMEM_`

This public reference tracks the memtomem 0.2.2 configuration surface.

Storage

Variable	Description	Default
`MEMTOMEM_STORAGE__BACKEND`	Storage backend	`sqlite`
`MEMTOMEM_STORAGE__SQLITE_PATH`	SQLite database file path	`~/.memtomem/memtomem.db`
`MEMTOMEM_STORAGE__COLLECTION_NAME`	Logical collection name	`memories`

Embedding

Variable	Description	Default
`MEMTOMEM_EMBEDDING__PROVIDER`	`none` / `onnx` / `ollama` / `openai`	`none` (keyword-only until wizard runs)
`MEMTOMEM_EMBEDDING__MODEL`	Model name for the chosen provider	`""`
`MEMTOMEM_EMBEDDING__DIMENSION`	Vector dimension (must match model)	provider-specific
`MEMTOMEM_EMBEDDING__BASE_URL`	Ollama / OpenAI-compatible endpoint	—
`MEMTOMEM_EMBEDDING__API_KEY`	API key for paid providers	—
`MEMTOMEM_EMBEDDING__BATCH_SIZE`	Texts per embedding batch	`64`
`MEMTOMEM_EMBEDDING__MAX_CONCURRENT_BATCHES`	Max parallel embedding batches	`4`
`MEMTOMEM_EMBEDDING__THREADS`	ONNX Runtime thread cap (`0` = ORT default)	`4`
`MEMTOMEM_EMBEDDING__PROGRESS_THRESHOLD`	Emit per-chunk progress only when a file produces more chunks than this threshold; `0` always emits	`32`

Indexing

Variable	Description	Default
`MEMTOMEM_INDEXING__MEMORY_DIRS`	Directories reactively re-indexed by the `mm server` file watcher (JSON list). Pre-existing files are not auto-scanned — seed them once with `mm index <dir>`, then the watcher picks up further edits. Populated by `mm init` when you opt in to AI agent memory enrollment.	`["~/.memtomem/memories"]` plus selected provider folders
`MEMTOMEM_INDEXING__PROJECT_MEMORY_DIRS`	Project-tier memory roots under `.memtomem/memories` or `.memtomem/memories.local`	`[]`
`MEMTOMEM_INDEXING__SUPPORTED_EXTENSIONS`	File extensions to index (JSON list)	`[".md", ".json", ".yaml", ".yml", ".toml", ".py", ".js", ".ts", ".tsx", ".jsx"]`
`MEMTOMEM_INDEXING__MAX_CHUNK_TOKENS`	Maximum tokens per chunk	`512`
`MEMTOMEM_INDEXING__MIN_CHUNK_TOKENS`	Merge threshold for short chunks	`128`
`MEMTOMEM_INDEXING__AUTO_DISCOVER`	When `true`, `mm init` prompts to enroll AI agent memory directories into `memory_dirs`. Set `false` to skip the prompt.	`true`
`MEMTOMEM_INDEXING__EXCLUDE_PATTERNS`	`.gitignore`-syntax patterns (JSON list) that stack on top of the built-in credential denylist (`oauth_creds.json`, `credentials`, `id_rsa`, `.pem`, `.key`, `.ssh/**`, …). User `!negation` cannot override the built-in secret patterns.	`[]`
`MEMTOMEM_INDEXING__TARGET_CHUNK_TOKENS`	Greedy semantic-pack target for short sibling sections. Set `0` to disable the pack pass.	`384`
`MEMTOMEM_INDEXING__CHUNK_OVERLAP_TOKENS`	Token overlap between adjacent chunks	`0`
`MEMTOMEM_INDEXING__STRUCTURED_CHUNK_MODE`	JSON/YAML/TOML chunking mode: `original` or `recursive`	`original`
`MEMTOMEM_INDEXING__PARAGRAPH_SPLIT_THRESHOLD`	Split long prose into paragraphs above this token count	`800`
`MEMTOMEM_INDEXING__STARTUP_BACKFILL`	On server start, run a one-shot scan over `memory_dirs` to catch files added while the server was down	`false`
`MEMTOMEM_INDEXING__AUTO_SUMMARIZE`	Generate AI per-source summaries when LLM is configured	`false`
`MEMTOMEM_INDEXING__SUMMARY_LANGUAGE`	Output language for AI source summaries	`en`
`MEMTOMEM_INDEXING__SUMMARY_MAX_INPUT_CHARS`	Max source chars sent to the summary LLM	`3000`
`MEMTOMEM_INDEXING__SUMMARY_MAX_TOKENS`	Summary output token cap	`256`

Namespace Policy Rules

Path-glob → namespace mappings that auto-tag files at index time, so you don’t pass namespace= on every mem_index call.

Variable	Description	Default
`MEMTOMEM_NAMESPACE__RULES`	JSON list of `{path_glob, namespace}` objects. `pathspec.GitIgnoreSpec` patterns, case-insensitive. `{parent}` and `{ancestor:N}` placeholders expand from the matched file path. Resolution order: explicit `namespace=` param → rules (first match) → `enable_auto_ns` → `default_namespace`.	`[]`
`MEMTOMEM_NAMESPACE__DEFAULT_NAMESPACE`	Default namespace for new chunks	`default`
`MEMTOMEM_NAMESPACE__ENABLE_AUTO_NS`	Derive namespace from a file’s immediate parent folder when no explicit namespace or rule applies	`false`

Example (via config.d/namespace.json, APPEND-merged):

{"namespace": {"rules": [
  {"path_glob": "docs/**", "namespace": "docs"},
  {"path_glob": "projects/{parent}/**", "namespace": "proj/{parent}"}
]}}

Reranking

Cross-encoder reranking runs fully locally by default — no external API required.

Variable	Description	Default
`MEMTOMEM_RERANK__ENABLED`	Enable reranking of hybrid search results	`false`
`MEMTOMEM_RERANK__PROVIDER`	`fastembed` (local ONNX) / `cohere` (external API)	`fastembed`
`MEMTOMEM_RERANK__MODEL`	Model name. Use `jinaai/jina-reranker-v2-base-multilingual` for non-English content.	`Xenova/ms-marco-MiniLM-L-6-v2`
`MEMTOMEM_RERANK__API_KEY`	Only required when `provider=cohere`	—
`MEMTOMEM_RERANK__OVERSAMPLE`	Pool multiplier over `response_top_k`. Pool size is `max(min_pool, min(max_pool, int(oversample * response_top_k)))`.	`2.0`
`MEMTOMEM_RERANK__MIN_POOL`	Floor — reranker never sees fewer candidates than this	`20`
`MEMTOMEM_RERANK__MAX_POOL`	Cap — prevents runaway cost at large `top_k`	`200`
`MEMTOMEM_RERANK__TOP_K`	Deprecated legacy pool size; migrates to `min_pool` when present	`20`

Search

Variable	Description	Default
`MEMTOMEM_SEARCH__DEFAULT_TOP_K`	Default result count	`10`
`MEMTOMEM_SEARCH__BM25_CANDIDATES`	BM25 candidate pool size	`50`
`MEMTOMEM_SEARCH__DENSE_CANDIDATES`	Dense vector candidate pool size	`50`
`MEMTOMEM_SEARCH__RRF_K`	Reciprocal Rank Fusion constant	`60`
`MEMTOMEM_SEARCH__ENABLE_BM25`	Enable keyword retriever	`true`
`MEMTOMEM_SEARCH__ENABLE_DENSE`	Enable semantic vector retriever	`true`
`MEMTOMEM_SEARCH__RRF_WEIGHTS`	RRF weights for `[BM25, Dense]` (JSON list, REPLACE merge)	`[1.0, 1.0]`
`MEMTOMEM_SEARCH__TOKENIZER`	FTS tokenizer: `unicode61` or `kiwipiepy`	`unicode61`
`MEMTOMEM_SEARCH__CACHE_TTL`	Search result cache TTL in seconds	`30.0`
`MEMTOMEM_SEARCH__SYSTEM_NAMESPACE_PREFIXES`	Namespace prefixes hidden from default `namespace=None` search (JSON list, APPEND merge)	`["archive:", "agent-runtime:"]`

Decay (time-based scoring)

Half-life decay multiplier applied to hybrid-search scores. Gradually deprioritises older chunks.

Variable	Description	Default
`MEMTOMEM_DECAY__ENABLED`	Enable time-based decay weighting	`false`
`MEMTOMEM_DECAY__HALF_LIFE_DAYS`	Half-life in days — a chunk’s contribution halves every interval	`30.0`

MMR (diversity rerank)

Maximal Marginal Relevance rerank. Reduces redundancy among top results and mixes in alternate angles.

Variable	Description	Default
`MEMTOMEM_MMR__ENABLED`	Enable MMR diversity rerank	`false`
`MEMTOMEM_MMR__LAMBDA_PARAM`	0.0–1.0. `0.0` = max diversity, `1.0` = max relevance	`0.7`

Access (frequency boost)

Frequency-based multiplier that promotes chunks which have been accessed often.

Variable	Description	Default
`MEMTOMEM_ACCESS__ENABLED`	Enable access-frequency boost	`false`
`MEMTOMEM_ACCESS__MAX_BOOST`	Score multiplier ceiling (must be `>= 1.0`)	`1.5`

Importance (metadata boost)

Multiplier derived from chunk metadata features (tags, size, position, …) applied on top of the search score.

Variable	Description	Default
`MEMTOMEM_IMPORTANCE__ENABLED`	Enable importance boost	`false`
`MEMTOMEM_IMPORTANCE__MAX_BOOST`	Score multiplier ceiling (must be `>= 1.0`)	`1.5`
`MEMTOMEM_IMPORTANCE__WEIGHTS`	Importance-feature weight vector (JSON list, REPLACE merge)	`[0.3, 0.2, 0.3, 0.2]`

Query expansion

Augments the original query with related tags, headings, or LLM-generated terms to improve recall. strategy=llm uses the LLM section below.

Variable	Description	Default
`MEMTOMEM_QUERY_EXPANSION__ENABLED`	Enable query expansion	`false`
`MEMTOMEM_QUERY_EXPANSION__MAX_TERMS`	Max additional terms to append	`3`
`MEMTOMEM_QUERY_EXPANSION__STRATEGY`	`tags` / `headings` / `both` / `llm`	`tags`

Context window

Small-to-big retrieval: returns ±N adjacent chunks around each search hit. Useful for recovering fragmented context in long documents.

Variable	Description	Default
`MEMTOMEM_CONTEXT_WINDOW__ENABLED`	Enable context-window expansion	`false`
`MEMTOMEM_CONTEXT_WINDOW__WINDOW_SIZE`	±N adjacent chunks per hit (`0`–`10`)	`2`

LLM (summarisation · query-expansion backend)

Shared LLM backend used by query_expansion.strategy=llm, consolidation summaries, and other LLM-powered features.

Variable	Description	Default
`MEMTOMEM_LLM__ENABLED`	Enable LLM-powered features	`false`
`MEMTOMEM_LLM__PROVIDER`	`ollama` / `openai` / `anthropic` / compatible endpoint	`ollama`
`MEMTOMEM_LLM__MODEL`	Model name. Empty = provider-specific default	`""`
`MEMTOMEM_LLM__BASE_URL`	Endpoint URL	`http://localhost:11434`
`MEMTOMEM_LLM__API_KEY`	API key for paid providers	—
`MEMTOMEM_LLM__MAX_TOKENS`	Generation token cap	`1024`
`MEMTOMEM_LLM__TIMEOUT`	Request timeout in seconds	`60.0`

Tool exposure

Variable	Description	Default
`MEMTOMEM_TOOL_MODE`	`core` (9 tools total, including `mem_do`) / `standard` (37 incl. `mem_do`) / `full` (84)	`core`

Web UI

Variable	Description	Default
`MEMTOMEM_WEB__MODE`	`prod` (polished pages only) / `dev` (adds maintainer pages: Sessions, Namespaces, Health Report). `mm web --mode` and `mm web --dev` override this at launch.	`prod`

Lifecycle policies & webhooks

Variable	Description	Default
`MEMTOMEM_POLICY__ENABLED`	Run PolicyScheduler (auto_archive / auto_promote / auto_expire / auto_tag)	`false`
`MEMTOMEM_POLICY__SCHEDULER_INTERVAL_MINUTES`	Scheduler tick interval	`60.0`
`MEMTOMEM_POLICY__MAX_ACTIONS_PER_RUN`	Cumulative action cap per scheduled policy run	`100`
`MEMTOMEM_WEBHOOK__ENABLED`	Enable outbound webhooks for memory events	`false`
`MEMTOMEM_WEBHOOK__URL`	Webhook target URL	—
`MEMTOMEM_WEBHOOK__EVENTS`	Event types to send (JSON list, APPEND merge)	`["add", "delete", "search"]`
`MEMTOMEM_WEBHOOK__SECRET`	HMAC signing secret	—
`MEMTOMEM_WEBHOOK__TIMEOUT_SECONDS`	HTTP timeout	`10.0`

Consolidation schedule

Background job that periodically groups near-duplicate memories and compresses them into archive summaries.

Variable	Description	Default
`MEMTOMEM_CONSOLIDATION_SCHEDULE__ENABLED`	Run the consolidation scheduler	`false`
`MEMTOMEM_CONSOLIDATION_SCHEDULE__INTERVAL_HOURS`	Scheduler interval (hours)	`24.0`
`MEMTOMEM_CONSOLIDATION_SCHEDULE__MIN_GROUP_SIZE`	Minimum group size to consolidate	`3`
`MEMTOMEM_CONSOLIDATION_SCHEDULE__MAX_GROUPS`	Max groups processed per run	`10`

Health watchdog

Background loop for periodic health checks, orphan-record cleanup, and automatic maintenance.

Variable	Description	Default
`MEMTOMEM_HEALTH_WATCHDOG__ENABLED`	Run the health watchdog	`false`
`MEMTOMEM_HEALTH_WATCHDOG__HEARTBEAT_INTERVAL_SECONDS`	Heartbeat interval	`60.0`
`MEMTOMEM_HEALTH_WATCHDOG__DIAGNOSTIC_INTERVAL_SECONDS`	Diagnostic-check interval	`300.0`
`MEMTOMEM_HEALTH_WATCHDOG__DEEP_INTERVAL_SECONDS`	Deep-scan interval	`3600.0`
`MEMTOMEM_HEALTH_WATCHDOG__MAX_SNAPSHOTS`	Snapshot retention cap	`1000`
`MEMTOMEM_HEALTH_WATCHDOG__ORPHAN_CLEANUP_THRESHOLD`	Orphan-record cleanup threshold	`10`
`MEMTOMEM_HEALTH_WATCHDOG__AUTO_MAINTENANCE`	Perform automatic maintenance	`true`

Scheduler

Variable	Description	Default
`MEMTOMEM_SCHEDULER__ENABLED`	Enable cron dispatch for registered maintenance jobs	`false`
`MEMTOMEM_SCHEDULER__MAX_CONCURRENT_JOBS`	Max concurrently running scheduled jobs	`1`
`MEMTOMEM_SCHEDULER__DEFAULT_TIMEZONE`	Schedule timezone; Phase A honors `utc`	`utc`
`MEMTOMEM_SCHEDULER__RUNNER_TIMEOUT_SECONDS`	Timeout for one scheduled job run	`300.0`

Session summary

Variable	Description	Default
`MEMTOMEM_SESSION_SUMMARY__AUTO`	Auto-generate an LLM summary on `mem_session_end` when enough chunks were added	`true`
`MEMTOMEM_SESSION_SUMMARY__MIN_CHUNKS`	Minimum chunks before auto-summary runs	`5`
`MEMTOMEM_SESSION_SUMMARY__MAX_SUMMARY_TOKENS`	Output token cap	`500`
`MEMTOMEM_SESSION_SUMMARY__MAX_INPUT_CHARS`	Skip auto-summary above this assembled input size	`60000`
`MEMTOMEM_SESSION_SUMMARY__MAX_SUMMARY_LINKS`	Cap summary-to-source chunk links	`50`
`MEMTOMEM_SESSION_SUMMARY__EXPANSION_LOOKUP_TOP_K`	Session-summary chunks considered for search rescue	`3`
`MEMTOMEM_SESSION_SUMMARY__EXPANSION_SCORE_THRESHOLD`	Minimum summary score for rescue expansion	`0.3`
`MEMTOMEM_SESSION_SUMMARY__EXPANSION_RESCUE_WEIGHT`	RRF input weight for rescued source-file hits	`0.5`

Logging

Variable	Description	Default
`MEMTOMEM_LOG_LEVEL`	`DEBUG` / `INFO` / `WARNING` / `ERROR`	`INFO`
`MEMTOMEM_LOG_FORMAT`	Log format	—

Hooks / Context Gateway

Variable	Description	Default
`MEMTOMEM_HOOKS__TARGET_SCOPE`	Scope for memtomem-managed Claude Code settings hooks: `user`, `project_shared`, or `project_local`	`user`
`MEMTOMEM_CONTEXT_GATEWAY__KNOWN_PROJECTS_PATH`	Web UI project registry for Context Gateway	`~/.memtomem/known_projects.json`
`MEMTOMEM_CONTEXT_GATEWAY__EXPERIMENTAL_CLAUDE_PROJECTS_SCAN`	Reverse-decode `~/.claude/projects/<encoded>` directories into project roots	`false`
`MEMTOMEM_CONTEXT_GATEWAY__USER_TIER_ENABLED`	Show user-tier canonical artifacts in discovery responses	`false`

Embedding provider comparison

Provider	GPU	Cost	Notes
`onnx`	No	Free	Built-in via fastembed. ~270 MB on first run
`ollama`	No	Free	Requires Ollama. `ollama pull nomic-embed-text`
`openai`	No	Paid	Requires API key

Full list: configuration.md in the upstream repo.

STM (memtomem-stm) — prefix `MEMTOMEM_STM_`

STM settings are organized into six sections: a flat LOG_LEVEL, plus PROXY__*, SURFACING__*, HOOK__*, DAEMON__*, and LANGFUSE__*. Compression, caching, metrics, auto-indexing, and extraction all live under PROXY__.

General

Variable	Description	Default
`MEMTOMEM_STM_LOG_LEVEL`	Log level	`WARNING`
`MEMTOMEM_STM_ADVERTISE_OBSERVABILITY_TOOLS`	When `true`, advertises the eight observability tools (`stm_proxy_stats`, `stm_proxy_health`, `stm_proxy_cache_clear`, `stm_surfacing_stats`, `stm_compression_stats`, `stm_progressive_stats`, `stm_index_stats`, `stm_tuning_recommendations`) in MCP `tools/list`. When unset/`false`, the four model-facing tools stay advertised and observability tools remain callable from Python.	`false`

Proxy

Variable	Description	Default
`MEMTOMEM_STM_PROXY__ENABLED`	Master switch for the proxy pipeline	`false`
`MEMTOMEM_STM_PROXY__DEFAULT_COMPRESSION`	Default compression strategy	`auto`
`MEMTOMEM_STM_PROXY__DEFAULT_MAX_RESULT_CHARS`	Per-response char budget	`16000`
`MEMTOMEM_STM_PROXY__MAX_UPSTREAM_CHARS`	OOM guard on upstream response size	`10000000`
`MEMTOMEM_STM_PROXY__MIN_RESULT_RETENTION`	Retention floor (0.0–1.0)	`0.65`

Proxy → Cache

Variable	Description	Default
`MEMTOMEM_STM_PROXY__CACHE__ENABLED`	Enable response caching	`true`
`MEMTOMEM_STM_PROXY__CACHE__DEFAULT_TTL_SECONDS`	Cache TTL	`3600`
`MEMTOMEM_STM_PROXY__CACHE__DB_PATH`	Cache DB location	—
`MEMTOMEM_STM_PROXY__CACHE__MAX_ENTRIES`	Cache eviction ceiling	—

Proxy → Auto-Index (Stage 4)

Variable	Description	Default
`MEMTOMEM_STM_PROXY__AUTO_INDEX__ENABLED`	Index tool responses into LTM	`false`
`MEMTOMEM_STM_PROXY__AUTO_INDEX__BACKGROUND`	Run Stage 4 off the request path (F4)	`false`
`MEMTOMEM_STM_PROXY__AUTO_INDEX__MIN_CHARS`	Minimum response size to index	—
`MEMTOMEM_STM_PROXY__AUTO_INDEX__MEMORY_DIR`	Output directory	—
`MEMTOMEM_STM_PROXY__AUTO_INDEX__NAMESPACE`	Namespace for auto-indexed memories	`proxy-{server}`

In the standalone mms server, auto_index and extraction are currently inert because no FileIndexer engine is wired at startup. Enabling these fields is valid config, but it does not write back to LTM until the MCP-only adapter is available.

Proxy → Metrics / Extraction / Relevance scorer

Variable	Description	Default
`MEMTOMEM_STM_PROXY__METRICS__ENABLED`	Record call metrics	`true`
`MEMTOMEM_STM_PROXY__EXTRACTION__ENABLED`	Stage 4b EXTRACT (fact extraction)	`false`
`MEMTOMEM_STM_PROXY__RELEVANCE_SCORER__SCORER`	Scorer backend	—
`MEMTOMEM_STM_PROXY__COMPRESSION_FEEDBACK__ENABLED`	Persist `stm_compression_feedback`	`true`
`MEMTOMEM_STM_PROXY__PROGRESSIVE_READS__ENABLED`	Record progressive-delivery read telemetry (surfaces via `stm_progressive_stats`)	`true`
`MEMTOMEM_STM_PROXY__LOCK_TIMEOUT_SECONDS`	Internal lock-acquisition ceiling; a timeout signals a deadlock/stuck holder rather than a slow upstream	`30.0`

Proxy → Timeouts

These live on per-upstream UpstreamServerConfig entries in ~/.memtomem/stm_proxy.json (set per server, not via env vars). Defaults apply to every registered upstream unless overridden.

Field	Description	Default
`call_timeout_seconds`	Per-attempt timeout for `session.call_tool()`. On timeout the session is force-reset and the retry loop proceeds.	`90.0`
`overall_deadline_seconds`	Total wall-clock budget across all retry attempts. Prevents `call_timeout × (max_retries+1)` worst-case blowout.	`180.0`
`compression.llm.llm_timeout_seconds`	Timeout for `llm_summary` compression; on timeout STM falls back to `truncate`.	`60.0`

Surfacing (Stage 3)

Variable	Description	Default
`MEMTOMEM_STM_SURFACING__ENABLED`	Enable proactive surfacing from LTM	`true`
`MEMTOMEM_STM_SURFACING__MIN_SCORE`	Minimum relevance score	`0.03`
`MEMTOMEM_STM_SURFACING__MAX_RESULTS`	Max memories injected per call	`3`
`MEMTOMEM_STM_SURFACING__MIN_RESPONSE_CHARS`	Skip surfacing on tiny responses	`5000`
`MEMTOMEM_STM_SURFACING__MIN_QUERY_TOKENS`	Min tokens in extracted query	`3`
`MEMTOMEM_STM_SURFACING__DEDUP_TTL_SECONDS`	Cross-session dedup window	`604800` (7 days)
`MEMTOMEM_STM_SURFACING__FEEDBACK_ENABLED`	Accept `stm_surfacing_feedback`	`true`
`MEMTOMEM_STM_SURFACING__AUTO_TUNE_ENABLED`	Per-tool threshold auto-tuning	`true`
`MEMTOMEM_STM_SURFACING__QUERY_RETENTION_DAYS`	Days to retain raw query text in the feedback DB before clearing the column; `0` disables cleanup	`30`
`MEMTOMEM_STM_SURFACING__PERSIST_QUERY_TEXT`	Store raw query text when `true`; store `sha256:<16-hex>` digests when `false`	`true`
`MEMTOMEM_STM_SURFACING__FEEDBACK_DEMOTION_ENABLED`	Locally filter memories with repeated negative feedback before injection	`true`
`MEMTOMEM_STM_SURFACING__FEEDBACK_DEMOTION_NEGATIVE_THRESHOLD`	Distinct negative surfacing events before local demotion applies	`3`
`MEMTOMEM_STM_SURFACING__LTM_MCP_TRANSPORT`	LTM MCP transport: `stdio`, `sse`, or `streamable_http`	`stdio`
`MEMTOMEM_STM_SURFACING__LTM_MCP_COMMAND`	MCP command launching the LTM server for stdio transport	`memtomem-server`
`MEMTOMEM_STM_SURFACING__LTM_MCP_ARGS`	Args for the LTM command (JSON list)	`[]`
`MEMTOMEM_STM_SURFACING__LTM_MCP_URL`	LTM endpoint URL for `sse` / `streamable_http`	`""`
`MEMTOMEM_STM_SURFACING__LTM_MCP_HEADERS`	Optional static headers for network LTM transport (JSON object)	`null`

Injection mode (append default, plus prepend / section) is set via MEMTOMEM_STM_SURFACING__INJECTION_MODE.

Hook / Daemon

Variable	Description	Default
`MEMTOMEM_STM_HOOK__USE_DAEMON`	Route `mms hook` surfacing through the warm local daemon instead of a cold in-process path	`true`
`MEMTOMEM_STM_HOOK__DAEMON_TIMEOUT_SECONDS`	Hook-to-daemon round-trip timeout	`2.5`
`MEMTOMEM_STM_HOOK__FALLBACK`	Behavior when daemon is unavailable: `skip` or `cold`	`skip`
`MEMTOMEM_STM_HOOK__AUTO_SPAWN`	Fire-and-forget spawn a daemon on the first eligible hook call	`true`
`MEMTOMEM_STM_HOOK__RECORD_FEEDBACK_EVENTS`	Persist hook surfacing feedback/query events; default keeps dedup without storing raw query text	`false`
`MEMTOMEM_STM_HOOK__COMPRESSION__ENABLED`	Enable built-in Bash `updatedToolOutput` compression	`false`
`MEMTOMEM_STM_HOOK__COMPRESSION__MAX_CHARS`	Target char budget for Bash output replacement	`16000`
`MEMTOMEM_STM_DAEMON__HOST`	Local daemon bind address; keep loopback-only	`127.0.0.1`
`MEMTOMEM_STM_DAEMON__IDLE_TIMEOUT_SECONDS`	Stop the daemon after this many idle seconds; `0` disables idle shutdown	`900.0`

Langfuse (observability)

Variable	Description	Default
`MEMTOMEM_STM_LANGFUSE__ENABLED`	Emit spans	`false`
`MEMTOMEM_STM_LANGFUSE__PUBLIC_KEY`	Langfuse public key	—
`MEMTOMEM_STM_LANGFUSE__SECRET_KEY`	Langfuse secret key	—
`MEMTOMEM_STM_LANGFUSE__HOST`	Langfuse host URL	—
`MEMTOMEM_STM_LANGFUSE__SAMPLING_RATE`	0.0–1.0	`1.0`

Setting MEMTOMEM_STM_LANGFUSE__ENABLED=true without the [langfuse] extra installed raises a ValueError at startup (fail-fast since v0.1.16). Install the extra first, or leave enabled=false. The old silent-disable-with-WARNING behavior is gone, so a typo no longer leaves tracing quietly off.

Compression strategies (`MEMTOMEM_STM_PROXY__DEFAULT_COMPRESSION`)

Strategy	Use for
`auto`	Default — picks per content type
`hybrid`	Markdown (structure + summarize non-essentials)
`selective`	Keep only query-relevant sections
`progressive`	Large content; cursor-based delivery (zero loss)
`extract_fields`	JSON dictionaries
`schema_pruning`	Large JSON arrays
`skeleton`	API docs (schema-only)
`llm_summary`	LLM-based summarization (Ollama / OpenAI)
`truncate`	Fallback truncation
`none`	Pass-through