Aidimag

AI Dimag — Verified Memory for AI Coding Agents

Your coding agent forgets your codebase. AIDimag doesn't.

Documentation • Why AIDimag? • Getting Started • Use Cases • Benchmarks • AI Dimag Cloud • Pricing

What is AI Dimag?

AI Dimag is a memory system for software engineering — not a general-purpose "AI memory" app. It gives any MCP-compatible agent (Claude, Cursor, Copilot, Windsurf…) a persistent memory of your codebase that survives across sessions — decisions, conventions, gotchas, failed approaches, guardrails, and reusable skills — stored as falsifiable claims with grounding evidence in .aidimag/ next to your code.

The subject of memory is your repository, not your preferences or chat history. Every capability — evidence, git-hook verification, guardrails, pre-commit checks, path-scoped recall, session scratchpad — exists to serve day-to-day development work.

The Difference: Claim-and-Verify, Not Store-and-Retrieve

Most memory systems store text and retrieve whatever is similar later — a stored fact is assumed true forever. That's dangerous in a codebase, where a confidently-retrieved stale fact is *worse* than no memory at all.

Every AI Dimag memory carries evidence (a shell check, an anchored commit, a test) that dim verify re-runs against the current repo — automatically, via git hooks, on every pull, checkout, and rebase. Beliefs that stop being true go STALE instead of silently misleading your AI.

Works with Every AI Tool

• MCP tools (Claude, Cursor, etc.) get real-time memory via the MCP server
• Non-MCP tools (Copilot, Windsurf, etc.) get static context files (.cursorrules, CLAUDE.md, AGENTS.md, etc.)

Install

npm install -g aidimag

Requires Node 22+. Ships two equivalent binaries: dim (short) and aidimag.

Quick Start

cd your-repo

dim init # creates .aidimag/, installs additive git hooks dim bootstrap # optional: LLM-survey the repo into a starter memory set dim review # approve what enters memory (nothing is stored unreviewed)

dim remember "All DB access goes through src/db/store.ts" -k INVARIANT -p src \ -e "STATIC_CHECK:! grep -rl better-sqlite3 src --include=*.ts | grep -v store.ts" dim recall db access dim verify # re-run all evidence; stale beliefs get flagged dim brief # session-start briefing: in-scope memory, guardrails, gaps

For non-MCP tools (Copilot, Cursor without MCP, etc.):

dim generate-context --format all --auto # creates .cursorrules, CLAUDE.md, AGENTS.md, etc.

One-command setup

dim setup --yes              # init + git hooks + MCP configs for detected agents + context files

dim setup-ollama # install Ollama + pull a free local embedding model for semantic search dim doctor # verify everything is wired correctly

Connect to Your AI Agent (MCP)

Add to your agent config (e.g. .mcp.json for Claude Code):

{

"mcpServers": { "aidimag": { "command": "npx", "args": ["-y", "aidimag", "mcp"], "env": { "AIDIMAG_REPO": "/path/to/your/repo" } } } }

MCP Tools get memory_search, memory_propose, context_note (live in-chat fact capture), chat_harvest (live, tool-agnostic session harvesting with server-side secret redaction), memory_critique (a second critic grounded in verified memory), session-start briefings, session-end extraction, and more.

Non-MCP Tools: dim generate-context -f all renders verified memory into .cursorrules, CLAUDE.md, AGENTS.md, .windsurfrules, and .github/copilot-instructions.md (--auto keeps them refreshed).

Hermes Agent: dim hermes install registers aidimag as a native Hermes memory provider — one command, no pip, no venv. A single stdlib-only Python bridge delegates to the MCP server: session briefings are injected into the system prompt, recall is prefetched per turn, and session learnings become review-queue *proposals* (never silent writes). Then: hermes config set memory.provider aidimag.

Key Features

Human-Gated Capture

Commits, PRs, AI-chat transcripts (Claude Code, Codex, Copilot, Cursor), and pasted docs are mined into *proposals*. Nothing enters memory until you approve it in dim review (auto-triaged best-first, approve all --min-score 0.7 for batches).

Verification Lifecycle

STATIC_CHECK / COMMIT_REF / TEST_RESULT / EXEC_TRACE / HUMAN_ATTESTED evidence. Failing evidence flips memories to STALE and auto-drafts a recovery proposal. Confidence decays without re-confirmation.

Evidence Trust Gate

Shell-command evidence that arrives via team sync is never executed until you inspect and approve it (dim verify --trust).

Hybrid Semantic Recall

FTS5 keyword + vector KNN (OpenAI, local Ollama, or AWS Bedrock; auto-detected except Bedrock, which is explicit opt-in; works keyword-only with none).

Guardrails & Skills

Behavioral rules (never / ask-first / always) and step-by-step procedures, enforced by dim check (pre-commit) and memory_critique.

Team Mode, Self-Hosted

dim serve + dim sync: local-first replicas, device-code login, brain-scoped API keys, hashed credentials, cross-machine verification consensus.

Knowledgebase Inbox

Drop design docs / ADRs / PDFs / DOCX into knowledge/ and they're summarized into reviewed, pinned memories.

Scratchpad & Provenance Audit

dim scratch (and the scratchpad_* MCP tools) hold short-term session notes — TTL-expiring, never synced, never durable memory. dim audit lists memories resting on the weakest ground (agent-authored, evidence-free, stale, or long-unverified) so you can fix them up like a dependency audit for your repo's knowledge.

Web Dashboard & Extensions

dim ui — run checks, session briefings, bootstrap, harvest, and context generation from the browser — plus VS Code and IntelliJ extensions.

Ticketing Integration

Commits tell you *what* changed; tickets hold the *why*. aiDimag connects to your ticketing system so that context flows into your memory — ticket titles, types, and statuses appear next to mined proposals during dim review, and agents can fetch tickets via the ticket_get MCP tool.

Supported providers

Jira, GitHub Issues, Linear, GitLab Issues, Azure DevOps, ClickUp, Shortcut, YouTrack, Asana, Trello, Notion, Pivotal Tracker, a custom HTTP middleware, or Remote (team sync server — zero local credentials).

Quick start

# Connect a provider (interactive)

dim ticket connect

Check status

dim ticket status

View a specific ticket

dim ticket show XXX-2100

Share credentials with your team (admin)

dim ticket share

Per-repo credential storage

Ticket credentials are stored per-repo in .aidimag/config.json under tickets.token (with file mode 0o600), matching the same pattern as cloud sync tokens. Credentials never leak between projects. You can also set the AIDIMAG_TICKET_TOKEN environment variable, which takes precedence over the config file.

Team-shared tickets (Remote provider)

One admin shares their ticket credential via the sync server (dim ticket share). Team members select "Remote (team sync server)" as their provider — they resolve tickets through the server and hold zero ticket credentials locally. When a cloud server is linked, the dashboard auto-discovers the team's ticket provider and shows a "Connect now" button.

Branch conventions

Define a branch-naming convention and have aiDimag warn or block on violations:

dim ticket branch-rule        # manage the convention

dim branch XXX-2100 # create a conforming branch (fetches title for slug)

Full guide: [Connecting tickets](https://aidimag.com/guides/tickets)

How It Compares

AI Dimag follows a claim-and-verify model; other memory systems follow store-and-retrieve. The short version:

Full comparison: [aidimag.com/comparison](https://aidimag.com/comparison)

vs. named tools

How aiDimag relates to the memory tools people usually ask about. These solve a different problem (remembering *users and conversations*); aiDimag remembers your *repository* and proves its memories are still true:

| Local-first | ✅ SQLite per repo | ✅ SQLite | ⚠️