Continuum

Persistent memory for AI agents, exposed as an MCP server. Connect Claude Code, Claude.ai, or any MCP client, and it remembers your preferences, decisions, and project context across sessions instead of starting from zero every time.

Quick start

Use the hosted instance — no setup required:

1. Sign up at continuum.sshogunn.org.

2. Connect a client:

   • Claude Code: claude mcp add --transport http continuum https://continuum-mcp.sshogunn.org/mcp

   • Claude.ai: Settings → Connectors → Add custom connector → https://continuum-mcp.sshogunn.org/mcp

3. Optional — install the Claude Code hooks so memory gets injected into every prompt automatically (no tool call needed) and durable facts from your sessions are saved for you:

   # macOS / Linux / WSL / Git Bash
   curl -fsSL https://continuum-mcp.sshogunn.org/install_hook.js | node

   # Windows PowerShell
   irm https://continuum-mcp.sshogunn.org/install_hook.js | node -

   The installer prints a short code and opens the dashboard's /device page — approve it there and the install finishes on its own. Each machine gets its own session (a 1-hour access token plus a refresh token the hooks rotate automatically), listed under Connections → Signed-in devices where you can sign it out. Needs Node 18+ on PATH (same requirement as Claude Code itself). On a machine with no browser, generate a token on the Connections page and pass it as CONTINUUM_TOKEN=<token> instead.

Both connect paths go through OAuth — no token to copy/paste anywhere.

Prefer to run your own instance? See Self-hosting.

Related MCP server: Playwright MCP Server

What it does

• Persistent memory — save, search, list, append and delete entries, scoped per user and per project workspace (every workspace is searched together with default).

• Recall tiers — always (standing rules, injected every message), relevance (surfaced on semantic match), manual (explicit lookup only).

• Knowledge graph — every saved memory is extracted in the background into entities and relationships. Each relationship is a one-sentence fact with its own embedding, returned alongside matching memories by memory_search. Facts that a newer memory contradicts are marked no-longer-true rather than deleted.

• Auto-injected context — an optional Claude Code hook injects relevant memory into every prompt without the model deciding to call a tool, and never repeats what the session has already been shown.

• Session capture — the same hook install captures durable facts from your sessions (before compaction and at session end) and saves them directly, merging into existing entries instead of duplicating them.

• OAuth 2.0 — PKCE flow with dynamic client registration, verified working with Claude.ai.

Full breakdown of how the memory pipeline and hooks work: docs/architecture.md.

MCP tools

Web search, page fetching and screenshots are left to the client's built-in tools. Export, import and archiving live in the dashboard.

Self-hosting

Continuum is a normal Docker Compose stack. It's MIT-licensed — clone it and run your own instance instead of (or alongside) the hosted one.

1. Create a Clerk application — auth runs on Clerk (free tier is enough). From the API Keys page, grab:

• CLERK_SECRET_KEY and CLERK_PUBLISHABLE_KEY → backend/.env

• the same publishable key as VITE_CLERK_PUBLISHABLE_KEY → frontend/.env

2. Generate secrets:

openssl rand -hex 32   # → POSTGRES_PASSWORD (root .env)
openssl rand -hex 32   # → REDIS_PASSWORD (root .env)
openssl rand -hex 32   # → CONTINUUM_INTERNAL_SECRET (must match in backend/.env and core-mcp/.env)

# RS256 keypair backend mints MCP tokens with, core-mcp verifies with
openssl genrsa -out /tmp/continuum_jwt 2048
openssl rsa -in /tmp/continuum_jwt -pubout -out /tmp/continuum_jwt.pub

# each printed as one line with literal \n, ready to paste into the .env files below
awk 'NF {printf "%s\\n", $0}' /tmp/continuum_jwt      # → backend/.env CONTINUUM_BACKEND_JWT_PRIVATE_KEY
awk 'NF {printf "%s\\n", $0}' /tmp/continuum_jwt.pub  # → core-mcp/.env CONTINUUM_JWT_PUBLIC_KEY
rm /tmp/continuum_jwt /tmp/continuum_jwt.pub

3. Fill in the .env files:

cp core-mcp/.env.example core-mcp/.env
cp backend/.env.example backend/.env
cp frontend/.env.example frontend/.env

Fill in the Clerk keys and generated secrets/keypair above — each file's comments say what's required vs optional. You'll also need an LLM API key for CONTINUUM_FACT_EXTRACTION_API_KEY (fact extraction) — any litellm-supported provider works.

4. Run it:

docker compose up -d --build

This starts frontend (:3000, or FRONTEND_PORT from the root .env), backend (:8789), core-mcp (:8788), plus worker, postgres and redis — all reachable on localhost, no extra setup. postgres also publishes to 127.0.0.1:5432 for a host-local client. Schema migrations (alembic upgrade head) run automatically on boot.

The frontend image is a static Vite build served by nginx, so its VITE_* values from frontend/.env are baked in when the image is built. After changing them, rebuild with docker compose up -d --build frontend.

To expose it beyond localhost, put a reverse proxy (Caddy, nginx, Traefik) in front of ports 3000/8789/8788, or set CF_TUNNEL_TOKEN in the root .env and run docker compose --profile tunnel up -d --build to use the built-in Cloudflare Tunnel instead — that container only starts when the tunnel profile is requested. Either way, once you have a public URL, update VITE_BACKEND_URL (frontend), CONTINUUM_FRONTEND_URL / CONTINUUM_BACKEND_PUBLIC_URL (backend), and CONTINUUM_BACKEND_PUBLIC_URL / VITE_CONTINUUM_MCP_URL (core-mcp / frontend) to match, then rebuild.

First run: visit the frontend and sign up — that's your account — then connect a client as in Quick start, pointing at your own URLs instead of the hosted ones.

Running a service outside Docker

cd core-mcp && uv sync
uv run alembic upgrade head
uv run python -m app.server

cd core-mcp && uv run arq app.worker.WorkerSettings   # background jobs: graph build, session capture

cd backend && uv sync && uv run alembic upgrade head && uv run python main.py

cd frontend && pnpm install && pnpm dev

Tests

cd core-mcp && PYTHONPATH=. uv run pytest tests   # hook context assembly, capture merge rules, storage
node --test hooks/test/hooks.test.js              # hook scripts against a fake server

Repo layout

core-mcp/
  app/
    server.py         # FastMCP app, MCP tools, /hook/* and /internal/* routes
    worker.py         # arq worker: graph build, session capture, log pruning
    auth.py           # JWT verification + revocation polling
    infra/            # pg.py, db.py, redis.py, browser_pool.py
    memory/           # memory.py, search.py, prompt.py (hook context), capture.py,
                      # kg.py / extract.py / resolve.py / edges.py (knowledge graph),
                      # hook_session.py, embeddings.py, llm.py
  alembic/            # schema migrations
  tests/
backend/
  app/                # FastAPI routes, OAuth, token management
  alembic/
frontend/
  src/pages/          # Vite SPA — dashboard, oauth-connect, landing
  nginx.conf          # static serving + SPA fallback for the Docker image
hooks/                # Claude Code hooks, installer, updater (Node, no deps) + tests
docker-compose.yml    # all services — secrets come from the .env files, see .env.example

Environment variables

Each service has an .env.example with inline comments for every variable. Notably:

• core-mcp: CONTINUUM_DATABASE_URL, CONTINUUM_JWT_PUBLIC_KEY, CONTINUUM_FACT_EXTRACTION_MODEL / _API_KEY (litellm model string).

• backend: DATABASE_URL, Clerk keys, CONTINUUM_BACKEND_JWT_PRIVATE_KEY (paired with core-mcp's public key).

• frontend: VITE_CLERK_PUBLISHABLE_KEY, VITE_BACKEND_URL (called cross-origin with CORS), VITE_CONTINUUM_MCP_URL (shown in the dashboard's connect/install commands). Read at build time.

• root: POSTGRES_PASSWORD, REDIS_PASSWORD, FRONTEND_PORT (optional), and (optional, tunnel profile only) CF_TUNNEL_TOKEN.

License

MIT