@memofs/mcp-server

~ ls .memofs/

Store decisions, facts, and context as simple markdown files in your project — versioned, portable, and always there when the next session starts.

cursor: cur_0x4f02a9

digest: sha256

[mount: file-first]

The Problem

AI Agents memory is broken in two directions.

On one side, static markdown rulebooks like AGENTS.md, CLAUDE.md and .cursor/rules bloat context windows with massive token dumps that silently drift the moment project files, docs, data schemas, or implementations change.

On the other side, hosted vector databases lock learned facts inside proprietary black boxes, invisible, impossible to review in a git diff, disconnected from your project, and trapped in someone else's cloud.

Silent Project Drift.

When project files, schemas, docs, or code change, unanchored memories reference deleted assets and obsolete facts, turning into toxic ghost context that actively steers AI into hallucinations.

The Black-Box Silo.

Proprietary vector databases lock learned knowledge behind opaque APIs. You can't inspect what the AI learned, edit it in your local editor, or review it in a git diff alongside your project.

The Prompt-Bloat Dilemma.

Static rulebooks (like 50KB instruction files) burn thousands of prompt tokens on every turn, while AI models forget to query dynamic memory unless the runtime deterministically pushes it.

Runtimes

One engine, three storage modes

MemoFS is built on a unified store abstraction. Choose where your memory resides based on your workflow and access needs.

RUNTIME 01Offline First

Local Mode Diagram

Local Storage Mode

All memory is stored directly on your project's filesystem as versioned markdown and JSON. Zero network latency, fully offline, and 100% git-trackable.

RUNTIME 02Cloud Sync

Hybrid Mode Diagram

Hybrid Sync Mode

Sub-millisecond local execution with automatic cloud replication. Your agent memory follows you across multiple machines, desktop workstations, and teammates.

RUNTIME 03Zero Local Files

Hosted MCP Diagram

Hosted MCP Endpoint

MemoFS Cloud hosts the runtime directly. Remote agents, ephemeral CI/CD containers, and serverless bots connect via standard MCP endpoint URL and API key.

Features & Capabilities

Engineered for autonomous agent memory

From sub-millisecond local hybrid recall to self-healing project anchors and multi-agent coordination. Built with transparent files, deterministic logic, and zero black boxes.

FEATURE 01Drift Defense

Code Anchoring & Drift Detection

Project Anchoring & Drift Detection

Memories bind directly to project files, research documents, data schemas, byte hashes, and symbol paths. When underlying assets change, query-time drift detection automatically demotes stale memory relevance before it causes hallucinations.

FEATURE 02Gated Fusion

Hybrid Recall & Fusion

Hybrid Recall & Gated Fusion

Sub-millisecond BM25 lexical keyword matching fused with dense vector embeddings via bounded gated-bonus ranking. Unifies memory chunk identity to eliminate duplicate hits and avoid LLM context bloat.

FEATURE 03Graph Native

Entity Graph & Consolidation

Entity Graph & Causal Provenance

Extracts entities, relationships, and causal lineage (memofs why) into transparent nodes.jsonl and edges.jsonl files. Deterministic and critic-gated consolidation merges redundant facts and traces decisions back to source evidence.

FEATURE 04Isolated Context

AgentFS Workspace Scratchpads

AgentFS Workspace Scratchpads

Isolated scratch filesystem per agent turn with outcome-gated memory promotion (success, failure, aborted). Automatically preserves and promotes high-signal durable facts while pruning intermediate session noise.

FEATURE 05Zero Omission

Agent Behavior Enforcement

Runtime Behavior Enforcement

Deterministic push hooks across 9+ AI tools and agent environments including Claude Code, Cursor, Copilot, Codex, and Gemini CLI. Automatically injects relevant memory context at session start, enforces project constraints, and preserves state across context compactions.

FEATURE 06Decay Floors

Cognitive Decay & Cold Archive

Cognitive Decay & Cold Archive

Memory-kind expiry windows age facts into unverified status without manual maintenance. Operator-guided consolidation moves superseded memories to cold archive with full forensic restoration.

FEATURE 07Coming Soon

Ephemeral Stream & Agent Pub/Sub

Ephemeral Stream & Agent Pub/Sub

Real-time append-only stream for transient cross-agent coordination (heartbeats, file intent, task status) and human steering hints. Filtered out of durable recall to eliminate noise, with automated TTL garbage collection on maintenance runs.

FEATURE 08Coming Soon

Procedural Memory & Playbooks

Procedural Memory & Playbooks

Actionable step-by-step workflow recipes and standard operating procedures stored as human-readable Markdown and structured JSON. Context strategist dynamically matches and surfaces relevant playbooks based on task type.

FEATURE 09Coming Soon

Static Memory Linter

Static Memory Linter

Semantic static analyzer CLI (memofs lint) for CI/CD pipelines. Detects contradictory assertions across stored notes, broken causal provenance links, dead project references, and orphaned knowledge graph entities before merge.

FEATURE 10Coming Soon

Visual Memory Studio

Visual Memory Studio

Local zero-dependency webview debugger for.memofs/. Inspect BM25 vs vector vs graph recall weight breakdowns, explore interactive entity graphs, and test snapshot rollback diffs in real time.

FEATURE 11Coming Soon

Vendor Memory Import

Vendor Memory Import & Setup

One command to bring your existing memory with you — import from developer tools, research agents, plus Mem0, Zep/Graphiti, Letta, and Cognee exports. Full offline file adapters write through the standard durable path with provenance and dry-run preview.

FEATURE 12Coming Soon

Immutable Action Receipts

Immutable Action Receipts

Append-only audit receipts capturing consequential AI actions, task correlation, causal parentage, reversibility metadata, argument digests, and before/after snapshot hashes for complete execution accountability.

Why File-First

MemoFS vs. Black-Box Memory

Most memory tools hide your data in opaque remote databases or rely on static rule files that drift and bloat prompt context. MemoFS combines deterministic local execution, project-anchored verification, and git-native transparency.

Dimension	MemoFS	Hosted Memory DBs
Where memory lives	✓Plain Markdown & JSONL files in.memofs/	✕Locked in a proprietary cloud database
Project drift detection	✓File hash, AST symbol & schema validation (memofs lint)	✕None; stale memories reference deleted assets & data
Behavior enforcement	✓Deterministic push hooks across 9+ AI tools & runtimes	✕Passive pull tools; relies on model to remember to search
Causal lineage & audit	✓Immutable action receipts & causal traversal (memofs why)	✕Opaque similarity scores; ephemeral chat logs lost
Inspect & edit	✓Any editor (VS Code, Cursor, Neovim, CLI)	✕Vendor web dashboard or raw unindexed file
Version control	✓Git-tracked & branchable alongside your project	✕Separate external database decoupled from project history
Context efficiency	✓Token-budgeted hybrid recall (BM25 + vector + graph)	✕Monolithic prompt bloat or noisy top-k embeddings
Offline execution	✓100% local-first; runs offline & in sandboxes	✕Requires persistent network & cloud API keys
Multi-agent coordination	✓Advisory file locks & standard stream schemas	✕Unsynchronized writes or heavy external daemons