Code has Git. Multi-agent reasoning does not.

Smriti is version control for project reasoning state — versioned, structured, branchable snapshots of what was decided, what's still open, and what each agent is doing right now. So multiple coding agents can coordinate on the same codebase without overwriting each other's thinking.

When you run multiple coding agents on the same project — Claude Code and Codex, or two Claude Code sessions — they share no state. Each agent starts from scratch, re-discovers decisions already made, and occasionally duplicates work another agent is already doing. The standard workaround is HANDOFF.md / NOTES.md. That works until reasoning needs to branch, be compared, be restored, or be validated against the actual repo. Smriti gives reasoning state the same primitives Git gives code — plus the coordination primitives Git doesn't have.

The Git analogy

Git preserves code history: what changed, when, by whom, on which branch. Smriti preserves project reasoning: what was decided, what's still open, what each agent is doing right now, and how the recorded state compares to the live repo.

The first five rows extend the Git analogy. The last three are coordination primitives Git doesn't have — because Git is built for one human committing serial code, and Smriti is built for multiple agents writing reasoning state in parallel.

Why markdown handoffs aren't enough

Markdown notes (HANDOFF.md, NOTES.md, etc.) can store free-form context — and for a solo developer working on one model, often that's enough. They start breaking the moment more than one agent needs to coordinate.

Markdown can store notes. It cannot reliably provide:

• Active claims — who is working on what right now, with a TTL
• Freshness checks — has the state moved since my base, before I checkpoint?
• Task IDs tied to claims — collision detection at the task level when agents pick up work
• Repo-state drift detection — recorded state vs the live repo, with N-commits-ahead / branch-mismatch surfacing
• Branchable, comparable, restorable reasoning — smriti fork, smriti compare, smriti restore
• A current-state surface — one well-defined brief multiple agents read at session start

The fundamental difference: markdown is prose. Smriti is structured, versioned, queryable state. Markdown describes what you were thinking; Smriti lets the next session pick up where you left off — without re-reading prose, without two agents redoing the same work, without lying about the repo.

Getting started

The core coordination loop runs entirely on a local SQLite file — no Docker, no API keys, no cloud required. API keys come in only for the optional LLM-assisted features (more below).

You'll need Python 3.11+ and Node 20.19+ / 22.12+.

1. Install (local-first)

git clone https://github.com/himanshudongre/smriti
cd smriti
make setup-local              # backend venv + CLI + frontend, no Docker

make setup-local creates a .env from the example, installs the backend, the CLI (smriti + smriti-mcp), and the frontend. The CLI binaries live in backend/.venv/bin/ — source backend/.venv/bin/activate puts them on your PATH.

Start the backend in one terminal and keep it running:

make dev-local                # backend on http://localhost:8000

In a second terminal, activate the CLI before running smriti commands:

cd smriti
source backend/.venv/bin/activate

Local mode stores state in SQLite at ~/.smriti/smriti.db. For a shared/team setup with Postgres, see Shared / team mode below.

For the chat UI, run make dev-frontend in a separate terminal and open http://localhost:5173.

2. Confirm install — smriti doctor

smriti doctor

Backend reachable, CLI/backend versions aligned, provider status. If anything's off, doctor tells you what.

3. See Smriti at work — smriti quickstart

smriti quickstart

Seeds a smriti-demo Space — one finished mini-project (a rate-limiting feature built by two agents, with a branch explored and dropped) — and prints a ~3-minute guided walkthrough. Works without API keys — quickstart seeds pre-built checkpoints, no live extraction. (For live --extract you need a real provider; see Provider configuration.) Clean up with smriti quickstart --remove.

4. Attach your own project — smriti init

cd into the project you want to attach. smriti init writes project-local files (skill packs, SessionStart hook, attachment record) into the current directory, so it attaches whichever project you're standing in — running it in the wrong directory attaches the wrong project.

cd /path/to/your-project       # your own project, not the Smriti repo
smriti init my-project

smriti init:

• creates a Space named my-project
• installs the Claude Code and Codex skill packs into the project
• writes the SessionStart hook for Claude Code
• writes .smriti.json at the repo root, binding this repo to the Space

The MCP config block smriti init prints is ready to paste into Claude Code, Cursor, or Windsurf. The shape:

{
  "mcpServers": {
    "smriti": {
      "command": "/absolute/path/to/smriti-mcp",
      "env": { "SMRITI_API_URL": "http://localhost:8000" }
    }
  }
}

Use the resolved path from smriti init rather than a bare "smriti-mcp" — a bare command name only works if it's on the MCP host's PATH, which a venv install usually isn't.

Use smriti attach <space> to bind (or re-bind) a repo to an existing Space without the full init.

Multiple projects. Attachment is per-project-directory, not global. Everything smriti init writes — .smriti.json, the SessionStart hook in .claude/settings.json, and the skill packs (.claude/skills/smriti/SKILL.md and AGENTS.md) — lives inside the project directory. Run smriti init once per project; the files for ~/code/project-a and ~/code/project-b never see each other. A Claude Code or Codex session opened in ~/code/project-a automatically lands on space project-a; the same agent opened in ~/code/project-b lands on project-b. The MCP server registration (the JSON block above) is machine-wide but stateless — every MCP call passes space="..." explicitly, so the server has no "current space" of its own.

5. Daily workflow — no <space> needed

Inside an attached repo, the everyday commands resolve the Space from .smriti.json:

smriti state                   # continuation brief — read first each session
smriti current                 # compact snapshot: direction, attention, open work
smriti metrics                 # project coordination KPIs

The SessionStart hook smriti init wrote will inject smriti state --compact at the start of each Claude Code session. The hook is space-agnostic — one hook works in every attached project.

The exact hook block (what smriti init writes into .claude/settings.json):

{
  "hooks": {
    "SessionStart": [
      {
        "matcher": "startup",
        "hooks": [
          {
            "type": "command",
            "command": "smriti state --compact 2>/dev/null || echo 'Smriti backend not reachable. Start it with: make dev-local'"
          }
        ]
      }
    ]
  }
}

Shared / team mode (Postgres)

Postgres remains the stronger shared/team backend — an explicit database service, Docker-backed state, and the closer path toward a hosted deployment.

cp -n .env.example .env
# In .env, set:
#   SMRITI_DB_MODE=postgres
#   DATABASE_URL=postgresql://smriti:smriti@localhost:5432/smriti

make setup-postgres              # starts Docker Postgres and runs migrations
make dev-postgres                # backend on http://localhost:8000
make dev-frontend                # frontend on http://localhost:5173

What you get

The primitives that turn "shared state" from a phrase into something that actually works for multiple agents:

• Versioned reasoning. Every checkpoint is a structured snapshot — objective, decisions, assumptions, tasks (with intent hints and IDs), open questions, entities, artifacts. Fork from any checkpoint to explore an alternative; smriti compare for a structured diff; smriti restore to return to a clean state. Pre-restore turns are excluded from context at the data layer, not just hidden.
• Active work claims. Agents declare intent before starting. Claims are advisory (not locks), time-bounded, and visible to every other agent via the state brief. Two agents see each other coming.
• Structured tasks + IDs. Checkpoint tasks carry optional intent_hint, blocked_by, status (open/done), and stable id slugs. Agents pick complementary work from the task list; claims can reference a specific task ID (--task-id impl-1) for precise collision detection when two agents start near-simultaneously.
• Freshness checks (--since). "Has the state moved since my base?" — checked before checkpointing, so an agent never writes on top of stale assumptions.
• Repo-state drift detection. smriti state compares the working git repo against the HEAD and branch the latest checkpoint recorded, surfacing dirty trees, detached HEAD, project-root mismatch, and N-commits-ahead-of-the-checkpoint signals. The reasoning state stops being "trust me" — it tells you when it may be stale.
• Project Current State (smriti current). A compact, packaged snapshot of where a project is right now: current direction, attention signals, active work, open tasks by intent, recent milestones, recent activity. Founder- and agent-facing.
• Worktrees. First-class git worktree primitive so multiple agents work on the same project without sharing one checkout. Each agent gets its own working tree; claims can bind to a worktree, and the state brief surfaces per-claim drift (branch, dirty count, ahead/behind vs origin/main).
• Backend capability manifest + smriti doctor. /health advertises the backend's feature surface so agents can detect a stale backend running old code; smriti doctor diagnoses backend reachability, runtime/code mismatches, and provider status.
• Destructive-action guards. Deleting a Space that still holds checkpoints requires an explicit --force (CLI), an echo-back confirm_space argument (MCP), or force=true (API). Real reasoning state cannot be wiped by one careless flag.

Four surfaces, one core

1. CLI (smriti) — how a coding agent reads and writes reasoning state from a shell tool loop.
2. MCP server (smriti-mcp) — the same surface as 21 MCP tools for Claude Code, Cursor, Windsurf.
3. Agent skill pack — versioned instructions teaching agents when to checkpoint (and critically when not to), when to fork, how to detect drift, and how to pick complementary work. Install once per project.
4. Chat UI — how a human reads, steers, and debugs shared state.

What Smriti is not

• Not an orchestrator. Smriti describes state. It does not assign tasks, schedule work, or route agents. Agents make their own decisions from shared metadata.
• Not a task manager. Tasks live inside checkpoints as structured fields. No separate task table, no Jira-like lifecycle, no assignment system.
• Not a memory database. Smriti stores structured reasoning snapshots at inflection points, not a running log of everything an agent said or saw.
• Not markdown. HANDOFF.md / NOTES.md handoffs work until you need claims, freshness, branching, drift detection, or coordination at all.
• Not production infrastructure (yet). Single demo user, no auth, no multi-tenancy. Works for solo builders running multi-agent workflows.

Provider configuration (LLM-backed features)

Smriti draws a hard line between core coordination (works with no API key) and LLM-backed features (require a configured provider).

Works with no key

• setup / doctor / quickstart
• smriti state / current / metrics
• claims (smriti claim, claim listing)
• attach / no-arg project workflow
• manual structured checkpoints (smriti checkpoint create <space> with a JSON payload on stdin)
• repo-state drift detection
• the chat UI's read-only dashboards (timeline, checkpoints, claims, drift signals)

Require a real provider

• smriti checkpoint create --extract — extracts structured fields from freeform markdown
• smriti checkpoint review — consistency review of a checkpoint
• checkpoint draft
• the chat UI's send loop — where the agent actually responds

Without a configured provider, these refuse to run rather than silently return placeholder content. --extract returns HTTP 412 Precondition Failed with an actionable error listing the configuration paths. Mock content is never silently committed into a real project — that would pollute reasoning state, which Smriti exists to keep trustworthy.

Configure a provider

Set one of these in .env (or your shell):

OPENAI_API_KEY=...
ANTHROPIC_API_KEY=...
OPENROUTER_API_KEY=...

Or, for a local OpenAI-compatible model (Ollama, LM Studio, vLLM, Together, etc.):

SMRITI_GENERIC_API_URL=http://localhost:11434/v1   # your local server
SMRITI_GENERIC_MODEL=llama3.1:8b
# SMRITI_GENERIC_API_KEY=not-required               # most local servers don't need one

Then set background_intelligence.provider: generic in backend/config/providers.yaml.

Extraction is a relatively lightweight structured-output task and is usually handled well by cost-efficient or local OpenAI-compatible models. That said, quality varies by model — validate with smriti checkpoint create --extract --dry-run on a representative document before relying on a small model for real work.

After configuring, run smriti doctor (optionally with --strict) to confirm the background provider line reads ready. --strict exits non-zero (EX_CONFIG / 78) if the provider is mock_or_disabled, which makes it safe to use in CI before any --extract step.

Mock mode

A deterministic MockAdapter exists for tests, demos, and the quickstart mechanics. It returns a fixed JSON blob (containing literal strings like "Mock decision from provider"). It is never the default for --extract — it only runs when the caller explicitly opts in (e.g. tests passing use_mock=true to the HTTP endpoint). Do not commit mock-extracted content into a real project Space.

Built with Smriti

The coordination substrate was built using Claude Code and Codex working in parallel on the same codebase, coordinating through Smriti's own state. smriti metrics smriti-dev:

• 117 checkpoints across 2 agents (Claude Code: 70, Codex: 47)
• 61 cross-agent continuations — checkpoints where a different agent picked up where the previous one left off
• 77 work claims at 96% completion — nearly every declared intent finished
• 7 milestones marking proven coordination proofs

The strongest proof: two agents started near-simultaneously, read the same task surface (4 tasks with stable IDs and intent hints), and independently picked different complementary tasks — one chose [test], the other chose [implement] — without any human routing. No orchestrator. No task queue. Just structured metadata on shared state.

What it looks like

Project timeline (dashboard)

Real project timeline from building Smriti with Smriti: summary panel, checkpoint cards with author badges, note indicators, needs-attention signal.

Agent-facing state and metrics (CLI)

What every agent reads at session start (smriti state --compact) and the project health KPIs (smriti metrics).

Structured checkpoint detail

The autonomy milestone checkpoint — structured tasks with intent badges, task IDs, and a founder milestone note annotating the first clean autonomous complementary-work proof.

Core concepts

• Space — a container for a line of work. Holds checkpoints and sessions. One project, one Space.
• Checkpoint — a structured snapshot of reasoning state (title, objective, summary, decisions, assumptions, tasks with intent hints and IDs, open questions, entities, artifacts). Created at inflection points — not after every small step.
• Session — a live conversation runtime inside a Space. Can be forked from any checkpoint.
• Claim — a lightweight, time-bounded declaration that an agent is working on something. Advisory, not a lock. Carries intent_type and optional task_id.

Context modes

• FRESH — blank state, no context
• HEAD — latest checkpoint + recent turns
• RESTORED — specific checkpoint restored; pre-restore turns excluded at the data layer
• FORKED — checkpoint base + separate branch

Restored mode is where isolation actually works. Earlier conversation is not hidden or summarized — it is excluded.

Current limitations

• Single user only — no auth, no multi-tenancy
• No merging of divergent checkpoint branches
• No streaming responses
• No mobile UI

Tech stack

FastAPI · SQLAlchemy · PostgreSQL / SQLite · React + TypeScript + Vite

Docker (Postgres mode helpers)

make up       # start all services
make logs     # follow logs
make down     # stop all services

Try the demo

The fastest way to see Smriti work is smriti quickstart (Getting started, step 3). For a deeper single-user walkthrough — checkpoint / fork / compare — see demos/branching-reasoning-demo/.