Memory Fabric MCP server

Memory Fabric

<!-- mcp-name: io.github.elViRafa/memory-fabric -->

File-first, local-first memory layer for MCP-compatible AI coding assistants.

Memory Fabric gives AI tools like Claude Code, Cursor, and GitHub Copilot a consistent, project-aware context layer without locking you into one model, editor, cloud provider, or operating system.

Memory is stored as human-readable Markdown with YAML frontmatter. No vector database. No cloud account. No embeddings required.

Features

decisions.md, ...) are generated views rebuilt by Dreaming, never hand-written

• MCP-native: exposes memory tools through the standard Model Context Protocol
• File-first: Markdown files are the source of truth, inspectable and commit-ready
• Local-first: core reads and writes work offline
• Store-first: facts live in memory-store/, one per file; root maps (architecture.md,

no agent cooperation required — via an opt-in post-commit hook

• Captures itself: every git commit is recorded as episodic memory automatically —

as cleanly as their code, instead of conflicting on a shared timestamp line

• Git-native merge: an optional custom merge driver lets two branches' memory merge

flags citations that rotted

• Self-verifying: memories can cite the file/line/commit they depend on; ai-memory verify

the same error into one growing record instead of scattering near-duplicates

• Learns from failure: writefailurememory_tool deduplicates repeat occurrences of

• Secret-safe: API keys and credentials are redacted before writing
• Token-budget aware: assembles context within limits; never slices files mid-document
• Quality eval: scores memory usefulness and Dreaming before/after results locally
• Unicode-safe: works with any human language
• Graceful degradation: works without rg, git hooks, or Dreaming configured

Status

v1.4.1 — field-store write/read hygiene (live handoffs, query packs, doctor smells) on top of the local field diary. Live on PyPI. Core CLI and MCP tools work end-to-end. See ROADMAP.md for what shipped, what's in progress, and what's next.

Demo

The CLI and self-capture flow: initialize a project, write a memory as a plain Markdown file in your repo, and watch a git commit record itself as episodic memory with no agent cooperation. The cross-tool moment — an agent writes memory in one tool and a different tool reads it back — is storyboarded in DEMO.md for the full video.

Privacy — no telemetry

Memory Fabric never sends data anywhere. There is no account, no cloud, no analytics, no phone-home. The core read and write paths make no network calls at all; the only optional network requests are a PyPI version-drift check and an LLM-provider preflight, both of which you can turn off with --offline. Your memory is plain Markdown in your own git history — it never leaves your machine unless you push it.

An optional, off-by-default field diary can record operational counts on your machine after you run ai-memory diary approve. That is not the session journal, and it is not telemetry: nothing is transmitted. MEMORYFABRICDIARY=0 is a kill switch. This is a deliberate guarantee, not a default we might change.

Installation

From PyPI (recommended)

Requires Python ≥ 3.11.

pipx install memory-fabric          # CLI only
pipx install "memory-fabric[mcp]"   # CLI + MCP server

Or with plain pip (inside a virtual environment):

pip install memory-fabric          # CLI only
pip install "memory-fabric[mcp]"   # CLI + MCP server

Shortened. The full README is on GitHub.