engram

Engram

The second brain your AI agents read and write.

(real-time, full quality)

— no signup. Search retainer price and watch the retired note get withheld.

Engram is a self-hosted MCP server + dashboard that gives Claude Code, Cursor, Hermes, and any

Model Context Protocol agent **shared, long-term memory they read

_and write_ — over a plain, git-backed folder of markdown you own**. Built for the case a single

agent's memory never hits: a team running several agents against one brain.

Autonomous agents forget everything between sessions — and worse, they can't tell what they remember

is _still true_. An agent pulls an old README, a retired price, an API doc you changed months ago, and

quotes it with full confidence, because keyword and vector search both rank by resemblance, not truth.

Engram makes "is this still true" a first-class, written property: mark a fact superseded or

expired and search withholds it — and tells the agent what it skipped and why. Per-agent read/write

tokens and a git audit trail of who-wrote-what keep it sane when the writers are a fleet, not just you.

Unlike a headless memory store, you can watch it happen. A fast dashboard lets you **search your

brain, see exactly what every agent and teammate changed (with per-file diffs), jump back** into

recent notes, and curate it all — while agents read and write the same vault over one MCP endpoint. No

database: your `.md` files are the source of truth, git is the durable store, and an in-memory index

powers full-text search + a wikilink knowledge graph.

> Opinionated about _how_ it stores memory — git-backed markdown, no database, agents write (not

> just read), self-hosted. Unopinionated about _what_ you keep in it — any markdown vault, any folder

> structure, any MCP client. Point it at a fresh repo or your existing Obsidian vault: no import

> step, no lock-in.

**What it's for · How it compares · Features** ·

**Works with · Quick start · MCP tools** ·

**Deploy · FAQ · Contributing**

What it's for

• Shared memory for a team running multiple agents — one vault, many agents reading and writing

concurrently, with per-agent read/write tokens and a git audit trail of who changed what.

• Memory that knows what's still true — retire a price, a term, or a changed API doc and your agents

stop quoting it; they're told what they skipped and why. The failure a single agent's memory never fixes.

• Long-term memory for Claude Code and other coding agents — stop re-explaining your project every session.
• A self-hosted, Obsidian-compatible second brain exposed over MCP — your notes, your server, your git repo.
• Memory you can see, not a black box — a dashboard to search, watch (with diffs), and curate what your agents remember.
• Markdown RAG without the vector database — full-text search + a link graph over human-readable files.

How it compares

Most agent memory is built to answer *"what did I store about this?"* Engram is built to answer

*"what is still true about this?"* — a different question, and the one that bites when an agent

quotes a price you retired months ago.

The row that matters is the third one. Similarity search cannot tell a contradiction from a

duplicate — a retired price and a live one are textually identical, so the retired one often

*outranks* the live one by being longer and more detailed. That can't be fixed at read time, which

is why Engram writes the retirement down when it happens.

This exact pair ships in sample-vault/. Run bun dev, search acme price,

and watch the retired note get withheld with a reason.

Categories, not feature-by-feature audits of specific products, and accurate to the best of my

knowledge as of July 2026. If something here misrepresents a tool you maintain, open a PR — I'll fix it.

Features

• MCP server — 15 `brain_*` tools over one bearer-authenticated HTTP endpoint (`POST /api/mcp`,

streamable HTTP JSON-RPC). Connect any MCP client to a single URL. Per-agent token scopes:

a read-only token never even sees the write tools.

• Human dashboard — a search-first home, file tree, note viewer with **Obsidian callouts,

wikilinks, and backlinks, Preview / Edit / Split editor with autosave, ⌘K search + in-page keyboard

navigation, "jump back in" recents, and a force-directed knowledge graph**.

• Authority-aware search — ranking knows relevance, not truth, so a superseded note repeats your

query words as often as the live one. Every hit carries an authority (`authoritative` → `current`

→ `provisional` → `superseded` → `archived`) derived from the note's folder and frontmatter — so your

agents quote the locked doc, not the dead one. Markdown RAG that won't hand back yesterday's answer.

• Temporal validity + explainable rejection — mark a fact `superseded_by` another note or give it a

`valid_until` date, and search withholds it by default (even if it's `locked`) — then hands the

agent an `excluded` list of what it skipped, each with a reason (`"expired 2026-06-01"`). One atomic

`brain_supersede` retires the old fact and links the new one in a single commit, so add-and-retire

can't drift apart. This is the difference between an agent that *remembers* and one that knows what's

still true.

• Write-time contradiction guards — authority ranking fixes *reading*; these stop the vault

accepting the contradiction in the first place. Engram refuses to create a second live note on a

subject a live note already covers (the `acme-pricing-2026.md`-beside-`acme-pricing.md` bug) and

points the agent at `brain_supersede` instead; refuses to overwrite a note the caller hasn't read;

and warns when a `status:` isn't a word the ranking model knows, so a typo can't silently strip a

note's authority.

• Audit trail + access control — every write is attributed in git to the token or human that

made it, with expandable per-file diffs in the activity feed. Give an agent a read-only token

and it never even sees the write tools; a write token can create, edit, move, and archive.

• The Curator *(optional)* — Engram's built-in agent harness over your vault. Chat with your

notes (grounded answers, wikilink citations). Or hand `brain_capture` a rough dump — a meeting note, a

voice transcript — and an agentic loop searches what already exists, then files, merges, or archives

and returns a manifest of what it touched. It reads before it overwrites and never deletes. Opus /

Sonnet / Haiku, your key.

• Markdown-native — plain `.md` + YAML frontmatter + `[[wikilinks]]`. Drop in an existing

Obsidian vault and it just works.

• Git-backed — optional auto commit + push of every change. Full history, no lock-in, your data

lives in your repo.

• No database — files are the source of truth; an in-memory MiniSearch index + a ported wikilink

graph power search and backlinks. Nothing to provision.

• Multi-workspace — connect multiple vault repos (URL + token or GitHub OAuth), rename, switch the

active one, or remove them — all from the UI.

• Self-hosted — one Docker container. Railway / Render / Fly / any host with a volume.

Not serverless (it needs a persistent volume, a file watcher, and a long-running index).

• Team auth — Google SSO + email allowlist for the dashboard; per-agent bearer tokens — or **OAuth

for Claude.ai custom connectors** — for MCP, created/revoked in the UI. Secrets encrypted at rest.

• Runtime config — toggle git-sync and the Curator right from the home; manage commit author, keys,

and OAuth in Settings — no redeploy.

Works with

Any client that speaks the Model Context Protocol — one endpoint, bearer-token auth. Most-used first:

• **Claude Code** — Anthropic's agentic coding CLI
• Codex — OpenAI's coding agent (CLI + IDE)
• Hermes — always-on autonomous agent runtime
• openclaw — open-source coding agent
• Cursor — AI code editor
• Cline — VS Code agent
• Windsurf — agentic IDE
• Claude Desktop — Anthropic's desktop app
• …and any other MCP client — Continue, Goose, Zed, Amp, and the rest

If it speaks MCP, it can read and write Engram as shared memory.

Quick start

Want to poke at it first? **There's a live demo** — open,

no signup, resets a few times a day. Break it all you like.

bun install
bun dev            # http://localhost:3000 — runs against ./sample-vault

Point it at your own vault:

VAULT_DIR=/path/to/your/obsidian-or-markdown/vault bun dev

Two ways to run it

• Hosted mode (team): the dashboard + HTTP MCP server above — self-host it once, many agents and

teammates connect over `POST /api/mcp`. This is the main mode.

• Local mode (stdio): a plain stdio MCP server over a folder, no HTTP/auth/git — for a single

machine, Claude Desktop / Cursor, or a registry's Docker introspection:

bun run mcp:stdio /path/to/your/vault      # defaults to ./sample-vault

Same `brain_*` tools. Built from `Dockerfile.mcp`.

Each mode ships as its own image, and they are not interchangeable:

Deploying the stdio image as a web service is the one mistake worth calling out: it can only 502,

because there is nothing listening. It now refuses to start on a PaaS and tells you this instead.

MCP tools

Agents only ever see the active vault — no repo, workspace, or GitHub tools are exposed.

A `read`-scope token sees only the read tools. `brain_capture` appears only when the Curator is `full`.

Connect an agent (the dashboard → Connect page shows the exact command + token):

claude mcp add --transport http engram https:///api/mcp \
  --header "Authorization: Bearer "

Deploy

Runs anywhere you can run a Docker container with a persistent volume — Railway, Render, Fly, or your

own box. Serverless (Vercel) won't work: Engram holds a volume, a file watcher, and an in-memory

index that a serverless function can't keep alive.

1. Deploy this repo (root `Dockerfile`), mount a volume at `/data`, set `ENGRAM_DATA_DIR=/data`.

2. Connect your vault repo(s) in the dashboard (Workspaces) — by URL + token, or GitHub OAuth.

3. Sign in with Google, create MCP tokens on the Connect page, point your agents at the URL.

Most runtime config (git-sync, AI capture, GitHub OAuth, app name) is editable in the Settings

page — only auth/infra bootstrap vars live on the host. Full setup: **DEPLOY.md**.

• Railway: New Project → *Deploy from GitHub repo* → add a Volume at `/data`.
• Render: one-click via the bundled `render.yaml` (Docker + a `/data` disk).

Deploying from a prebuilt image instead of the repo? Use `ghcr.io/rwnalds/engram-app:latest` —

not `engram:latest`, which is the stdio server and cannot answer HTTP. Set the healthcheck to

`/api/health`.

FAQ

How do I give Claude Code long-term memory?

Deploy Engram, connect a markdown vault, and `claude mcp add` the endpoint. The `brain_*` tools let

Claude Code search, read, and write persistent notes across sessions.

Can multiple AI agents share one knowledge base?

Yes. Every agent points at the same MCP URL and reads/writes the same active vault — that's the point.

Give each agent its own bearer token, `read` or `write` — a read-only token can't mutate your notes.

How do I stop an agent from quoting outdated facts?

Retire the fact and search stops surfacing it. When a value changes, call `brain_supersede(old, new)` —

one atomic commit marks the old note `superseded_by` the new one, and it's **withheld from search by

default (even if it's `locked`). Or set `valid_until: 2026-12-31`** on a note and it self-expires.

Retired matches don't vanish silently: `brain_search` returns them in an `excluded` list with a

reason (`"expired 2026-06-01"`), so the agent can say *what it ignored and why* instead of quoting it.

What stops an agent just adding a second, contradicting note?

Engram refuses the write. Told "the price is now X", an agent that can't overwrite a note it never

read will happily *add* `acme-pricing-2026.md` next to `acme-pricing.md` — nothing is corrupted, and

you now have two live notes disagreeing about one number. That write is rejected with a pointer to

`brain_supersede`, which retires the old note and adds the new one in a single commit. Pass

`allow_conflict: true` when both notes genuinely belong.

How do I know what an agent changed?

Every write is committed to git attributed to the token or human behind it, and the dashboard's

activity feed shows per-file diffs — a built-in audit trail for autonomous agents.

Does it work with my Obsidian vault?

Yes. It reads plain markdown with frontmatter and `[[wikilinks]]`, and renders Obsidian-style callouts

and backlinks. No import step.

Do I need a vector database?

No. Engram uses full-text search (MiniSearch) plus a wikilink graph over human-readable markdown —

no embeddings service, no vector store to run.

Can I chat with my notes?

Yes — enable the optional Curator, a chat agent that searches and reads your vault to answer with

wikilink citations (Opus / Sonnet / Haiku). It's read-only in chat, so it helps you think without

changing anything, and it runs on your own Anthropic key.

Can I see what my agents changed?

Yes — the Activity view reads your vault's git history and shows every change (agents and teammates

alike), expandable to per-file diffs. Since it's just git, you get the full audit trail for free.

Is my data locked in?

No. It's just `.md` files in a git repo you own. Turn Engram off and you still have every note and its

full history.

Where does it run / is it self-hosted?

You host it. One Docker container on Railway / Render / Fly / any VM with a volume. Your keys, your data.

Contributing

Issues and PRs welcome — especially where the validity model breaks against a vault shaped

differently from mine.

• **CONTRIBUTING.md** — setup, conventions, and the pre-PR checklist.
• **docs/curator.md** — how the optional Curator agent loop works.
• **SECURITY.md** — please report vulnerabilities privately, not as an issue.

bun install && bun dev
bun test          # the ranking/authority suite, incl. the stale-truth fixtures

If Engram is useful to you, starring the repo genuinely helps other people find it.

Stack

Next.js 16 (App Router) · React 19 · TypeScript · Tailwind v4 · shadcn/ui · bun · MiniSearch ·

d3-force · MCP SDK. MIT licensed.

Keywords: MCP server · Model Context Protocol · second brain for AI agents · agent memory ·

long-term memory for Claude Code · shared memory for AI agents · self-hosted knowledge base ·

Obsidian-compatible · markdown · knowledge graph · wikilinks · PKM · Zettelkasten · git-backed notes ·

Hermes agent memory · Cursor memory · RAG without a vector database · chat with your markdown notes ·

git-backed agent activity feed · audit trail for AI agents · authority-aware search · read-only vs

write MCP tokens · agent access control · self-organizing notes · agentic note capture · AI that files

your notes · temporal validity · stale memory · agents quoting outdated facts · supersede · note expiry ·

shared memory for a team of agents · Basic Memory alternative · mem0 alternative.