Skip to main content
Glama

Engram

Engram is an epistemic engine for AI coding agents — not just memory. It persists facts with confidence, corroboration, and contradiction tracking across repositories, autonomously learns from outcomes, exposes everything over MCP, and replaces itself in your context window on a token budget.

Epistemic engine = contradiction detection + confidence-ranked retrieval + autonomous fact lifecycle + token-budgeted injection. Engram doesn't just store what you said — it tracks what's true, what conflicts, and what's worth remembering.


Quick start

npm install -g @tinydarkforge/engram
engram setup
claude mcp add engram -s user -- engram mcp

Engram is now available as a tool in every Claude Code session. It remembers what you did across every repository, ranks what it knows, and injects a budget-capped slice of context on demand.


How it works

Engram captures engineering work and stores it in two layers:

Session memory — Git-hook or manual engram remember saves notes, topics, diffs, and test deltas to a per-project index. Every repo on your machine gets its own namespace.

Assertion ledger — A SQLite-backed fact store. Every claim records confidence (0.0–1.0), status (tentative → established → fossilized), quorum count, decay model, lineage, and tension markers.

Autonomous Intelligence — Engram runs a background learning loop during consolidation. It automatically detects contradictions (tensions), promotes corroborated facts to established status, and fossilizes outdated knowledge without user intervention.

Retrieval

Queries traverse four layers, stopping at the earliest one that answers:

Layer

Size

Latency

Role

Bloom filter

243 B

~0.1 ms

Instant "not known" — zero tokens consumed

Session index

~4 KB

~10 ms

Compact summaries — answers ~80% of queries

Session detail

per-file

~5 ms

Full content, lazy-loaded on demand

Ledger

~2 KB/fact

5–15 ms

Ranked facts with confidence, quorum, tension

Results are packed into a caller-specified token budget using decay × status × quorum × tension × weight.

Semantic search uses a local ONNX embedding model (@huggingface/transformers) that loads lazily on the first semantic query. Text search and keyword recall work without it.


Install

npm install -g @tinydarkforge/engram
engram setup

From source

git clone https://github.com/tinydarkforge/Engram.git
cd Engram
npm install
npm run setup

Connect Claude Code

# Global install
claude mcp add engram -s user -- engram mcp

# Source install  
claude mcp add engram -s user -- node "$(pwd)/scripts/mcp-server.mjs"

Usage

# Save a session
engram remember "Implemented OAuth callback handling" --topics auth,oauth

# Interactive session capture
engram remember --interactive

# Search across all projects
engram semantic "authentication work"
engram search "oauth"

# One-shot query against the assertion ledger
engram ask "what do we know about authentication"   # new in v5

# Temporal compaction — fossilize low-signal assertions
engram compact   # new in v5

# View status and ledger health
engram status

# Launch the web dashboard
engram start   # → http://127.0.0.1:3000

Dashboard API

The dashboard exposes live metrics endpoints:

Endpoint

Returns

GET /api/stats

Session counts, projects, topic count

GET /api/dashboard/tensions

Unresolved contradictions with claims

GET /api/dashboard/velocity

Facts/day rate + 30-day sparkline data

GET /api/dashboard/consolidation

Last consolidation run time and tasks

GET /api/assertions

Paginated assertion browser

GET /api/assertions/:id

Full detail with outcomes, lineage, feedback

Background consolidation

Engram runs periodic consolidation (every 5 min) to close the learning loop:

ledger_scan    →  Detect new contradictions (tensions)
ledger_verify  →  Re-verify stale state_bound facts
counterfactual →  Recompute importance weights
post_hoc       →  Score assertion outcomes from sessions
auto_resolve   →  Auto-resolve tensions older than 30 days
ledger_transform → Promote/fossilize/weight assertions

Run a full cycle manually:

npm run consolidate:full   # --all including manifest + embeddings
node scripts/consolidate.js --all

MCP tools (available in Claude Code, OpenCode, Cursor, Aider, and Windsurf)

Engram exposes tools via MCP for session search, ledger ingestion, context selection, semantic recall, cross-project search, and agent handoff. Run engram mcp to start the MCP server, or configure any agent:

engram setup --agent claude       # Claude Code
engram setup --agent opencode     # OpenCode CLI
engram setup --agent cursor       # Cursor IDE
engram setup --agent aider        # Aider
engram setup --agent windsurf     # Windsurf

Features

Engram

Gentleman-Programming/engram (Go)

mem0

Letta / Zep

Local-first (no cloud)

Yes

Yes

No

No

Contradiction detection + auto-resolve

Yes

No

No

No

Confidence-ranked retrieval

Yes

No

No

No

Assertion ledger (confidence, quorum, status)

Yes

No

No

No

Autonomous consolidation (learning loop)

Yes

No

No

No

Post-hoc outcome scoring

Yes

No

No

No

Counterfactual importance weighting

Yes

No

No

No

Semantic recall (by meaning, not keyword)

Yes

No

No

Yes

Temporal compaction (fossilize low-signal)

Yes

No

No

No

Event-driven confidence adjustment

Yes

No

No

No

MCP-native (7+ agents)

Yes

No

No

No

Git-hook session capture

Yes

Yes

Partial

Partial

Token-budgeted retrieval

Yes

Yes

No

No

Semantic search (local ONNX)

Yes

No

Yes

Yes

Cross-session diff

Yes

No

No

No

Agent handoff

Yes

No

Limited

Limited

MCP Resources with subscriptions

Yes

No

No

No

Live dashboard (tension radar, velocity, etc.)

Yes

No

No

No


Prerequisites

  • Node.js >=20

  • macOS or Linux (Windows not supported — shell scripts and symlinks)

  • Semantic search downloads a ~100 MB ONNX embedding model on first query. Keyword search works without it.


Security

  • No network calls unless you opt in. The embedding model is downloaded once and cached locally. If you never invoke semantic search, nothing is fetched.

  • No telemetry. Engram never phones home.

  • Local files only. Session data lives under ~/.engram/summaries/ and the ledger DB in ~/.engram/.cache/engram.db.

  • Reporting vulnerabilities: see SECURITY.md.


Architecture

scripts/     Runtime, CLI, MCP servers, ledger, consolidation
web/         Dashboard UI (Express + static files)
tests/       29 test files (node:test)
schemas/     JSON schemas for sessions and ledger
migrations/  SQLite schema migrations
examples/    Curated session records

Engram runs two servers:

  • HTTP API + Dashboard (port 3000) — REST endpoints and web UI

  • MCP server (port 3001) — Streamable HTTP and stdio transports for Claude Code

Both can run simultaneously. The MCP server accepts optional API key authentication.


License

MIT — see LICENSE.


A
license - permissive license
-
quality - not tested
A
maintenance

Maintenance

Maintainers
4dResponse time
Release cycle
1Releases (12mo)
Issues opened vs closed

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tinydarkforge/Engram'

If you have feedback or need assistance with the MCP directory API, please join our Discord server