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TencentDB Agent Memory — Installation Guide

← Back to README.md · 简体中文: INSTALL_CN.md

This document covers three installation modes:

  1. Full three-in-one stack: memory-core + memory-hub + proxy in one shot (recommended — lets coding agents like Claude Code plug directly into your team memory / knowledge / skill injection).
  2. Memory Hub only: lightweight deploy when Memory Core is already running.
  3. Using Proxy with Claude Code: point a coding agent at the proxy.

Full three-in-one stack: Memory Core + Memory Hub + Proxy (recommended)

Boot memory-core + memory-hub + proxy in one command so coding agents can consume team memory / knowledge / skills through the proxy:

# 1) Fetch the scripts
git clone https://github.com/TencentCloud/TencentDB-Agent-Memory.git
cd TencentDB-Agent-Memory/deploy/global-images

# 2) Prepare .env (fill in real LLM values)
cp .env.example .env
$EDITOR .env
#   MEMORY_LLM_BASE_URL   / MEMORY_LLM_API_KEY   / MEMORY_LLM_MODEL     ← used internally by memory + hub
#   PROXY_UPSTREAM_URL    / PROXY_UPSTREAM_API_KEY / PROXY_UPSTREAM_MODEL ← upstream the proxy forwards to

# 3) Dry-run validation (optional; also does a live LLM probe — use --skip-llm to skip)
./verify.sh

# 4) One-shot boot
./start-all.sh

When it finishes, the script automatically:

  1. On the first boot, calls init-admin to create the admin user, generates a random 32-char user_key and persists it to ./.admin-key (reused across restarts of the same volume).

  2. Immediately runs POST /v3/meta/auth/verify to sanity-check the key. Once verified, it prints a ready-to-run block like:

    export ANTHROPIC_BASE_URL=http://127.0.0.1:8096/claude-code/default
export ANTHROPIC_AUTH_TOKEN='sk-mem-<random 32 chars>'
claude --model <whatever PROXY_UPSTREAM_MODEL is set to>

Default ports:

Service Port Purpose
Memory Core 8420 memory read/write, auth, skill/RAG data plane
Panel UI 8125 team memory control panel
Knowledge 8424 wiki / code-graph service
Proxy 8096 LLM request proxy (Anthropic / OpenAI dual-protocol)

After deploy: making it useful

Starting the containers is just half the job. To make coding agents like Claude Code actually consume team memory, you also need to (a) create the org structure in the panel and (b) pick them from within a CC session.

Step 1: Log into the panel

Open http://localhost:8125 in your browser (Panel UI).

  • The first visit asks for a user_key — use the admin one printed at the end of start-all.sh (stored in deploy/global-images/.admin-key, a sk-mem-... string)
  • Once logged in you are system_admin. It can create Teams and sub-users, but at this stage cannot directly create other business assets such as Agent / Wiki / Skill (the business APIs enforce owner_user_id === caller, and system_admin isn't yet in the allow-list; this restriction will be lifted in a future release).
  • Correct pattern: admin creates a normal user → copy that user's user_key → log out → log back in as the new user → everything from here on (Team / Agent / Task) is owned by the new user.

In short: admin is the "ops account" for managing users; business users are the "app accounts" for managing assets. Even in a single-machine local playground, keep this split — don't use the admin key to drive CC.

Knowledge Service Swagger (optional, for API poking): http://localhost:8424/docs

Step 1.5: Admin creates a business user (required once)

Panel: top-left "Users" → "New" (or use the API directly):

ADMIN_KEY=$(cat ./.admin-key)
curl -sS -X POST http://localhost:8420/v3/meta/user/create \
  -H "x-tdai-user-key: $ADMIN_KEY" \
  -H "x-tdai-service-id: default" \
  -H "Content-Type: application/json" \
  -d '{"username":"you"}' | jq

The response body's data.default_user_key (sk-mem-...) is the login key for the new user — save it now; the panel won't show the full value again after creation.

Then log out of the panel and log back in with this new key — you're now a normal user and can create Team / Agent / Task under your own name.

Step 2: Create Team / Agent / Task in the panel

Every memory entry attaches to a team / agent / task triple:

  1. Team: sidebar → "Team" → New
    • A Team owns everything: memory, skill, knowledge
  2. Agent: enter a Team → "Agent" → New
    • Fill a clear description + system prompt (the agent's role)
    • e.g. bug-fix engineer, frontend reviewer, SQL tuner
  3. Task (optional): Team → "Task" → New
    • A Task is the concrete piece of work: "fix login XSS", "ship v1.4"
    • Memories link to Tasks; skipping Task still works but L2/L3 lose the Task dimension

You'll want at least 1 Team + 1 Agent before you start; Task is optional.

Step 3: Point Claude Code at the Proxy

Use the business user's user_key (not the admin key — admin can't own assets yet, and proxy's sessionInit will show an empty picker):

export ANTHROPIC_BASE_URL=http://127.0.0.1:8096/claude-code/default
export ANTHROPIC_AUTH_TOKEN="<the sk-mem-... from Step 1.5>"
claude --model <whatever PROXY_UPSTREAM_MODEL is set to>
  • ANTHROPIC_BASE_URL reroutes CC's API from anthropic.com to the local proxy; the trailing default is the memory instance ID (x-tdai-service-id) — always default in this local deploy
  • ANTHROPIC_AUTH_TOKEN is the business user's user_key (the default_user_key returned in Step 1.5); proxy uses it to look up user_id via core, and only teams/agents/tasks owned by this user show up in the next step's picker
  • --model uses the upstream model name you configured in PROXY_UPSTREAM_MODEL (proxy forwards to PROXY_UPSTREAM_URL)

Step 4: First CC turn — pick Team → Agent → Task

Every new CC session, the proxy uses CC's native AskUserQuestion tool to walk you through three consecutive picks:

┌─────────────────────────────────────────────────┐
│  1. Please pick the Team for this session:     │
│     ○ Team A                                    │
│     ○ Team B                                    │
│                                                 │
│  2. Please pick an Agent under Team A:         │
│     ○ bug-fix engineer                         │
│     ○ frontend reviewer                        │
│                                                 │
│  3. Optionally pick a Task:                    │
│     ○ Fix login XSS                            │
│     ○ [Skip task binding]                      │
└─────────────────────────────────────────────────┘

Answer each with CC's usual arrow-key + Enter. Once done:

  • Proxy binds this session to that team/agent/task
  • Every subsequent turn, proxy auto-injects that agent's L2/L3 memory, skills, and knowledge into the system prompt
  • L0 (raw dialogue) is captured into memory-core's SQLite
  • Background workers extract L1 (memory) → L2 (scene) → L3 (persona) as thresholds are hit

Only a new CC session triggers the picker; subsequent turns inside the same claude process reuse the binding.

Step 5: Watch memory grow

After a chat, look in the panel:

  • Left sidebar → Memory → Chat Memory: L0 dialogue sliced into scenes
  • Agent detail page → Profile: L2 scenes + L3 persona accumulate
  • Skill list: if the LLM decides "this is a reusable how-to", it gets auto-extracted into a Skill

Memory-core /health also shows whether the pipeline is doing work:

curl -s http://localhost:8420/health | jq .services.pipelineWorker

Expect tasksConsumed / tasksCompleted to grow with dialogue.

FAQ

Q: CC session doesn't prompt me to pick anything? PROXY_ENABLE_SESSION_INIT=1 isn't set. start-all.sh defaults to PROXY_FULL_STACK=1 which enables it; if you overrode .env or ran PROXY_FULL_STACK=0, restart: PROXY_FULL_STACK=1 ./start-proxy.sh.

Q: The picker is empty (or only shows entries owned by someone else)? You're likely driving CC with the admin key. Admin cannot own business assets (current limitation), so its team list is empty. Fix: follow Step 1.5 to create a business user, then use that user's default_user_key as ANTHROPIC_AUTH_TOKEN. The business user must also have created at least one Team/Agent in the panel.

Q: Panel shows "Panel API 8125 not started"? docker ps and check tdai-memory-hub is healthy. If not, look at docker logs tdai-memory-hub — most commonly a mis-set REMOTE_INSTANCE_URL or LLM_BASE_URL.

Q: L1/L2 never runs, records/ stays empty? Default promptMode=chat extracts memory from ordinary conversation. If you set code but the dialogue is small talk, the LLM decides there is nothing worth persisting and returns 0. Switch back to chat or have a real work-style conversation with the agent (edit files, run tests, give conclusions).

Q: How do I switch to another team/agent mid-work? Start a fresh claude session (new window / new session ID) — the picker runs again.

Memory Hub only

When Memory Core is already running on port 8420, one command pulls the Memory Hub image so you get the team memory panel:

docker pull docker.io/agentmemory/memory-hub:latest

Boot Panel + Knowledge Service:

docker run -d --name tdai-memory-hub \
  --add-host=host.docker.internal:host-gateway \
  -p 8125:8125 -p 8424:8424 \
  -v tdai-panel-data:/data/knowledge \
  -e REMOTE_INSTANCE_URL=http://host.docker.internal:8420 \
  -e REMOTE_INSTANCE_KEY=local \
  -e KNOWLEDGE_PUBLIC_BASE_URL=http://host.docker.internal:8424/v3 \
  -e LLM_MODE=custom \
  -e LLM_BASE_URL=<OPENAI_COMPATIBLE_BASE_URL> \
  -e LLM_API_KEY=<YOUR_API_KEY> \
  -e LLM_MODEL=<MODEL_ID> \
  docker.io/agentmemory/memory-hub:latest

Open http://localhost:8125.

Using Proxy with Claude Code

start-all.sh has already stored the admin user_key at deploy/global-images/.admin-key. Point Claude Code straight at the proxy:

export ANTHROPIC_BASE_URL=http://127.0.0.1:8096/claude-code/default
export ANTHROPIC_AUTH_TOKEN="$(cat ./.admin-key)"
claude --model <whatever PROXY_UPSTREAM_MODEL is set to>

The proxy pipeline in order: auth (validates user_key) → sessionInit (interactive team/agent/task picker) → injection (L2/L3 memory + skill + knowledge blended into the system prompt) → forward to the upstream LLM.

Disable the full pipeline (passthrough only): PROXY_FULL_STACK=0 ./start-proxy.sh.

Stop / cleanup

./stop-all.sh            # stop containers, keep volumes & admin key
./stop-all.sh --purge    # nuke volumes, admin key, and generated proxy config

More

Additional installation modes (OpenClaw, Hermes, SDK, running from source, K8s, platform notes) — see deploy/global-images/README.md and MemoryCore/README.md.