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🧠 Live Memory — MCP Knowledge Live Memory Service

Shared working memory for collaborative AI agents

CI Docker Version License MCP Python

🇫🇷 Version française


📋 Table of Contents


🎯 Concept

Live Memory is an MCP (Model Context Protocol) server that provides Memory Bank as a Service for AI agents. Multiple agents collaborate on the same project by sharing a common working memory.

graph-memory  = LONG-TERM memory (documents → Knowledge Graph → Vector RAG)
live-memory   = WORKING memory (live notes → LLM → Structured Memory Bank)

Two Complementary Modes

Mode Description Analogy
🔴 Live Real-time notes (observations, decisions, todos...) append-only Shared whiteboard
📘 Bank LLM consolidation into structured Markdown files based on rules Structured project log

Why Live Memory?

Problem Live Memory Solution
Agents lose context between sessions bank_read_all → complete context in 1 call
Multi-agent collaboration is impossible Append-only notes, no conflicts, cross-visibility
Manual consolidation is tedious LLM transforms raw notes into structured documentation
Memory scattered in local files Central S3 point, accessible from everywhere
No link with long-term memory 🌉 Graph Bridge pushes the bank into a knowledge graph

🧠 Multi-agent Collaboration and Two-Level Memory Architecture

Recent research on LLM-based multi-agent systems (Tran et al., 2025 — Multi-Agent Collaboration Mechanisms: A Survey of LLMs) identifies shared memory as a fundamental component. In their formal framework, a multi-agent system is defined by agents (A), a shared environment (E), and collaboration channels (C). The authors emphasize that LLMs are inherently isolated algorithms, not designed to collaborate — they need a shared memory infrastructure to coordinate their actions.

Live Memory + Graph Memory directly implements this architecture:

┌─────────────────────────────────────────────────────────────┐
│                  Shared Environment E                       │
│                                                             │
│  ┌──────────────────┐   LLM   ┌──────────────────────┐      │
│  │   Live           │ ──────► │   Bank               │      │
│  │  Real-time notes │ consolid│  Structured working  │      │
│  │  (append-only)   │  -ates  │  memory              │      │
│  └──────────────────┘         └──────────┬───────────┘      │
│                                          │                  │
│                                     graph_push              │
│                                     (MCP Streamable HTTP)   │
│                                          │                  │
│                               ┌──────────▼───────────┐      │
│                               │  🌐 Graph Memory     │      │
│                               │  Knowledge Graph     │      │
│                               │  (entities, relations│      │
│                               │   embeddings, RAG)   │      │
│                               └──────────────────────┘      │
└─────────────────────────────────────────────────────────────┘
Level Service Duration Content Usage
Working Memory Live Memory Session / project Raw notes + consolidated Markdown bank Operational context, daily coordination
Long-term Memory Graph Memory Permanent Entities + relations + vector embeddings Searchable knowledge base in natural language

The Graph Bridge (graph_push) is the collaboration channel between these two levels. Following the late-stage collaboration pattern described in literature (sharing consolidated outputs as inputs to another system), it transforms working documentation (Markdown) into structured knowledge (entities/relations graph).

Why two levels? One level is not enough:

  • Working memory alone is ephemeral — it disappears when the project ends
  • Knowledge graph alone is too heavy for quick daily notes
  • The bridge between the two allows agents to work fast (live notes) while capitalizing knowledge (graph)

Specifically, agents can:

  1. Write quickly without friction (live-memory, append-only, ~50ms)
  2. Automatically consolidate via LLM into structured documentation (bank, ~15s)
  3. Persist knowledge in a searchable graph (graph-memory, ~2min)
  4. Query the graph in natural language to retrieve information from past projects

🏗️ Architecture

     Agent Cline        Agent Claude        Agent X
          │                   │                │
          └────────┬──────────┘                │
                   │                           │
                   ▼  MCP Protocol (Streamable HTTP)  ▼
          ┌────────────────────────────────────────┐
          │   Caddy WAF (Coraza CRS)               │
          │   Rate Limiting • TLS • OWASP CRS      │
          └────────────┬───────────────────────────┘
                       │
          ┌────────────┴───────────────────┐
          │   Live Memory MCP (:8002)      │
          │   43 tools • Auth Bearer       │
          │   LLM Consolidation            │
          └──────┬──────────┬──────┬───────┘
                 │          │      │
          ┌──────┴──┐  ┌────┴───┐  │
          │   S3    │  │ LLMaaS │  │  MCP Streamable HTTP
          │Dell ECS │  │ CT API │  │  (optional)
          └─────────┘  └────────┘  │
                       ┌───────────┴────────────┐
                       │   Graph Memory         │
                       │   (long-term memory)   │
                       │   Neo4j + Qdrant       │
                       └────────────────────────┘

Minimal Stack: S3 + LLM. No local database. Optional: connection to Graph Memory for long-term memory (knowledge graph).


📦 Prerequisites

  • Docker >= 24.0 + Docker Compose v2
  • Python 3.11+ (for CLI, optional)
  • A compatible S3 storage (Cloud Temple Dell ECS, AWS, MinIO)
  • An OpenAI API compatible LLM (Cloud Temple LLMaaS, OpenAI, etc.)

🚀 Installation

1. Clone the repository

git clone https://github.com/Cloud-Temple/live-memory.git
cd live-memory

2. Configure the environment

cp .env.example .env

Edit .env with your values (see Configuration).

3a. Docker Start (recommended)

# Build images (WAF + MCP server)
docker compose build

# Start services
docker compose up -d

# Check status
docker compose ps

# Health check
curl -s http://localhost:8080/health

3b. Local Start (development)

# Install dependencies
uv pip install -e .

# Run server
python -m live_mem

4. Install CLI (optional)

uv pip install -e .

5. Verify Installation

# Health check via CLI
python scripts/mcp_cli.py health

# Or full E2E test (creates space, writes notes, consolidates)
python scripts/test_recette.py

Exposed Ports

Service Port Description
WAF 8080 Only exposed port — Caddy WAF → Live Memory
MCP Server 8002 Internal Docker network only

⚙️ Configuration

Edit .env. All variables are documented in .env.example.

Mandatory Variables

Variable Description Example
S3_ENDPOINT_URL S3 endpoint URL https://takinc5acc.s3.fr1.cloud-temple.com
S3_ACCESS_KEY_ID S3 access key AKIA...
S3_SECRET_ACCESS_KEY S3 secret key wJal...
S3_BUCKET_NAME Bucket name live-mem
S3_REGION_NAME S3 region fr1
LLMAAS_API_URL LLM API URL (must include /v1) https://api.ai.cloud-temple.com/v1
LLMAAS_API_KEY LLM API key sk-...
ADMIN_BOOTSTRAP_KEY Admin bootstrap key (≥ 32 chars) my-secret-key-change-me

Optional Variables — LLM

The consolidator uses an LLM (OpenAI-compatible API) to transform live notes into structured bank files.

Variable Default Description
LLMAAS_MODEL qwen3.5:27b LLM model name as exposed by the provider
LLMAAS_CONTEXT_WINDOW 131072 TOTAL context window of the model (input + output combined, in tokens). Qwen3 235B = 128K
LLMAAS_MAX_TOKENS 16384 Max OUTPUT tokens per request. The consolidator adjusts dynamically: output = min(MAX_TOKENS, CONTEXT_WINDOW - input)
LLMAAS_TEMPERATURE 0.3 LLM creativity (0.0 = deterministic, 1.0 = very creative)
PROXY_URL (none) Outbound HTTP proxy (e.g. http://10.0.0.1:3128). Custom variable (not HTTP_PROXY) — injected manually into boto3 (S3) and httpx (LLM). Not supported for Graph Memory connections.

Optional Variables — Consolidation and Compaction

Variable Default Description
MCP_SERVER_PORT 8002 MCP server listening port
MCP_SERVER_DEBUG false Detailed logs (full error messages)
CONSOLIDATION_TIMEOUT 600 Timeout per LLM call (seconds)
CONSOLIDATION_MAX_NOTES 200 Max notes per consolidation
CONSOLIDATION_BATCH_SIZE 5 Notes per LLM batch (small = precise, large = faster)
CONSOLIDATION_COOLDOWN_SECONDS 60 Per-space anti-spam cooldown for bank_consolidate (0 disables)
CONSOLIDATION_VALIDATION_ENABLED false Optional post-consolidation check for unattributed claims
CONSOLIDATION_VALIDATION_MAX_EXAMPLES 20 Max examples returned by the validation pass
COMPACT_THRESHOLD 0.6 Auto-compaction trigger (0.6 = compact if bank > 60% of budget)
BANK_FILE_MAX_SIZE 15360 Max size per bank file (bytes, 15 KB). Above = compaction candidate
RESPONSE_MAX_BYTES 524288 Max non-MCP response body size before truncation
API_TOOL_MAX_BODY_BYTES 1048576 Max request body accepted by /api/tool

▶️ Getting Started

docker compose up -d
docker compose ps       # Check status
docker compose logs -f live-mem-service --tail 50  # Logs

🔧 MCP Tools

43 tools exposed via the MCP protocol (Streamable HTTP), divided into 7 categories.

System (3 tools)

Tool Parameters Description
system_health Health status (S3, LLMaaS, number of spaces)
system_whoami 👤 Current token identity (name, permissions, spaces)
system_about Service identity (version, tools, capabilities)

Space (9 tools)

Tool Parameters Description
space_create space_id, description, rules, owner? Creates a space with its rules (bank structure)
space_update space_id, description?, owner? Updates description and/or owner
space_update_rules space_id, rules 📜 Updates space rules (admin only)
space_list Lists spaces accessible by current token
space_info space_id Detailed info (notes, bank, consolidation)
space_rules space_id Reads immutable space rules
space_summary space_id Complete summary: rules + bank + stats (agent startup)
space_export space_id tar.gz export in base64
space_delete space_id, confirm Deletes the space (⚠️ irreversible, admin required)

Live (3 tools)

Tool Parameters Description
live_note space_id, category, content, tags? Writes a timestamped note (agent = token name). Categories: observation, decision, todo, insight, question, progress, issue
live_read space_id, limit?, category?, agent? Reads live notes (optional filters)
live_search space_id, query, limit? Full-text search in notes

Bank (11 tools)

Tool Parameters Description
bank_read space_id, filename Reads a bank file (supports subfolders: personaProfiles/buyer.md)
bank_read_all space_id Reads entire bank in one request (🚀 agent startup)
bank_list space_id Lists bank files with relative paths (without content)
bank_consolidate space_id, agent? 🧠 Enqueues async LLM consolidation. Call once; do not watch/poll unless explicitly requested
bank_consolidation_status job_id Manual-only status check for a job returned by bank_consolidate
bank_consolidation_queues space_ids? Read-only summary of consolidation lanes by space
bank_stale_spaces min_notes?=5, min_age_days?=5, space_ids? 🚨 Lists spaces with ≥N unconsolidated notes whose oldest is ≥D days old (supervision)
bank_compact space_id, dry_run? 🔧 Compacts oversized bank files via LLM. dry_run=True by default (admin)
bank_repair space_id, dry_run? 🔧 Repairs corrupted filenames (Unicode, parasitic prefixes). dry_run=True by default (admin)
bank_write space_id, filename, content ✏️ Writes/replaces a bank file directly — bypasses LLM consolidation (admin)
bank_delete space_id, filename 🗑️ Deletes a bank file + its Unicode duplicates (admin, irreversible)

Graph (4 tools) — 🌉 Link to Graph Memory

Tool Parameters Description
graph_connect space_id, url, token, memory_id, ontology? Connects a space to Graph Memory. Tests connection, creates memory if needed. Default ontology: general
graph_push space_id Synchronizes bank → graph. Smart delete + re-ingest, orphan cleanup. ~30s/file
graph_status space_id Connection status + graph stats (documents, entities, relations, top entities, documents list)
graph_disconnect space_id Disconnects (data remains in graph)

Backup (5 tools)

Tool Parameters Description
backup_create space_id, description? Creates a full snapshot on S3
backup_list space_id? Lists available backups
backup_restore backup_id Restores a backup (space must not exist)
backup_download backup_id Download as tar.gz base64
backup_delete backup_id Deletes a backup

Admin (8 tools)

Tool Parameters Description
admin_create_token name, permissions, space_ids?, expires_in_days?, email? Creates a token (⚠️ displayed only once). Permissions: read, write, admin. Optional email for traceability
admin_list_tokens Lists active tokens
admin_revoke_token token_hash Revokes a token (makes it unusable)
admin_delete_token token_hash Physically deletes a token from the registry (⚠️ irreversible)
admin_purge_tokens revoked_only? Bulk purge: revoked only (default) or all tokens
admin_update_token token_hash, space_ids, action Modifies token spaces (add/remove/set)
admin_bulk_update_tokens filters, delta, confirm? Bulk token update with filters and add/remove/set operations
admin_gc_notes space_id?, max_age_days?, confirm?, delete_only? Garbage Collector: cleans orphaned notes

🌉 Graph Bridge — Link to Graph Memory

⚠️ Architecture note (v2.5.0) — Live Memory + Graph Memory responsibility separation

  • Memory Bank (Live Memory) = compact session bootstrap. activeContext.md is a volatile focus snapshot, progress.md is a bounded recent journal. The consolidator continuously rewrites and compacts these files.
  • Graph Memory = durable semantic index for stable canonical documents (RFCs, incidents, runbooks, design docs, infrastructure inventories).
  • Repository files = final authority.

Graph Memory complements the bank; it does not replace it. Graph Memory localizes; canonical repository files confirm.

Therefore, graph_push is NOT a routine action: pushing the full bank into the graph teaches it transient content that a later compaction strands as stale. Routine flows should ingest canonical repository documents directly into Graph Memory from the agent / tooling layer, using stable source_path keys. graph_push remains available for one-off bootstrap and explicit debug / migration only.

In particular, activeContext.md and progress.md must never end up in Graph Memory. A future revision (tracked in DESIGN/live-mem/EVOLUTION_LIVE_GRAPH_INTEGRATION.md) will turn this into a server-side guardrail. See WORKSPACE_CLINE_ADVANCE_RULES.md for the agent-side template.

Live Memory can push its Memory Bank into a Graph Memory instance for long-term memory. The knowledge graph extracts entities, relations, and embeddings from bank files.

Workflow

1. graph_connect(space_id, url, token, memory_id, ontology="general")
   └─ Tests connection, creates Graph Memory if needed

2. bank_consolidate(space_id)
   └─ Queues async consolidation; call once and do not watch/poll unless explicitly requested

3. graph_push(space_id)
   ├─ Lists documents in Graph Memory
   ├─ For each modified bank file:
   │   ├─ document_delete (removes orphaned entities)
   │   └─ memory_ingest (complete graph recalculation)
   ├─ Cleans deleted bank documents
   └─ Updates metrics (last_push, push_count)

4. graph_status(space_id)
   └─ Stats: 79 entities, 61 relations, top entities, documents...

Smart Push (delete + re-ingest)

Each push is a complete refresh of the graph for that file. Existing files are deleted then re-ingested so Graph Memory recalculates entities, relations, and embeddings with up-to-date content.

Available Ontologies

Ontology Usage
general (default) Versatile: FAQ, specs, certifications, CSR
legal Legal documents, contracts
cloud Cloud infrastructure, product sheets
managed-services Managed services, outsourcing
presales Pre-sales, RFP/RFI, proposals

🖥️ Web Interface

Live Memory exposes a web interface on /live to visualize memory spaces in real-time.

Access

http://localhost:8080/live

Features

Zone Content
📊 Dashboard (left) Space info, consolidation (date + counters), live/bank stats, colored agents, categories with %, Markdown rules, Graph Memory
🔴 Live Timeline (top-right) Live notes grouped by date (Today/Yesterday/date), cards with agent + category + Markdown
📘 Bank Viewer (bottom-right) Consolidated file tabs, Markdown rendering with marked.js

Layout

┌──────────────┬────────────────────────────┐
│  📊 Dashboard│  🔴 Live Timeline          │
│  (info,      │  (auto-refresh, date group)│
│   agents,    ├────────────────────────────┤
│   rules...)  │  📘 Bank (Markdown tabs)   │
└──────────────┴────────────────────────────┘

Smart Auto-refresh

  • Configurable: 3s / 5s / 10s / 30s / manual
  • Anti-flicker: only re-renders DOM if data has changed
  • Pulsing green dot with last refresh timestamp
  • Space selection → immediate loading (no button needed)

REST API (5 endpoints)

Endpoint Description
GET /api/spaces List of spaces
GET /api/space/{id} Complete info (meta + rules + stats + graph-memory)
GET /api/live/{id} Live notes (filters: ?agent=, ?category=, ?limit=)
GET /api/bank/{id} Bank file list
GET /api/bank/{id}/{filename} Bank file content

/api/* endpoints require a Bearer Token. /live page and /static/* files are public.

Admin Console (/admin)

A full administration console is available at /admin, exposing all 43 MCP tools through a web interface:

http://localhost:8080/admin
Section Features
📊 Dashboard Health status (clickable → service details), spaces count, active tokens, version/uptime, identity bar
📂 Spaces CRUD, info/rules modals, explore link, delete with confirmation
🔑 Tokens Create/update/revoke/delete, visual space chips with delta calculation
🔍 Explorer Live notes + bank files side-by-side for any space
💾 Backups Create/restore/delete, "Backup All", dynamic columns
🌉 Graph Bridge Status check, push, disconnect per space
🧹 Maintenance Consolidate, compact, repair, GC, purge — single space selector, compact action list
  • Auth: requires a valid token (same as /live), session via HttpOnly cookie
  • CSP-safe: zero inline handlers, all via data-action + event delegation
  • Upload Rules: file picker (.md) or paste directly from the Rules modal

🔌 MCP Integration

📖 Full Guide: See CLINE_INTEGRATION_GUIDE.md for the step-by-step guide (Cline configuration, custom instructions, workflow, multi-agents, troubleshooting). Equivalent guides exist for CLAUDE_CODE_INTEGRATION.md and CODEX_INTEGRATION.md.

With Cline (VS Code / VSCodium)

In Cline's MCP settings (cline_mcp_settings.json):

{
  "mcpServers": {
    "live-memory": {
      "url": "http://localhost:8080/mcp",
      "headers": {
        "Authorization": "Bearer lm_YOUR_TOKEN"
      }
    }
  }
}

To configure the Custom Instructions for your agent, copy one of the two workspace rule templates into your Cline global Custom Instructions (or into a .clinerules/ directory in your project):

Template When to use
WORKSPACE_CLINE_RULES.md Workspaces with Live Memory only.
WORKSPACE_CLINE_ADVANCE_RULES.md Workspaces also connected to Graph Memory (Graph-first lookup, compaction discipline, agent-side ingestion).

Customize a few placeholders ({LIVE_MCP_SERVER}, {SPACE}, and for the advanced template {GRAPH_MCP_SERVER} / {GRAPH_MEMORY_ID}). The agent name is auto-detected from the authentication token — nothing else to configure.

💡 Ready-to-use templates: WORKSPACE_CLINE_RULES.md (Live-only) and WORKSPACE_CLINE_ADVANCE_RULES.md (Live + Graph) — copy and customize the placeholders.

📖 Detailed integration guides: CLINE_INTEGRATION_GUIDE.md, CLAUDE_CODE_INTEGRATION.md, CODEX_INTEGRATION.md.

With Claude Desktop

In claude_desktop_config.json:

{
  "mcpServers": {
    "live-memory": {
      "url": "http://localhost:8080/mcp",
      "headers": {
        "Authorization": "Bearer lm_YOUR_TOKEN"
      }
    }
  }
}

Via Python (MCP client)

from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession

async def example():
    headers = {"Authorization": "Bearer your_token"}
    async with streamablehttp_client("http://localhost:8080/mcp", headers=headers) as (r, w, _):
        async with ClientSession(r, w) as session:
            await session.initialize()

            # Load all context
            result = await session.call_tool("bank_read_all", {
                "space_id": "my-project"
            })

            # Write a note
            await session.call_tool("live_note", {
                "space_id": "my-project",
                "category": "observation",
                "content": "Build passing in CI"
            })

💻 CLI and Shell

CLI Installation

pip install click rich prompt-toolkit mcp[cli]>=1.8.0
export MCP_URL=http://localhost:8080
export MCP_TOKEN=your_token

CLI Commands (Click)

python scripts/mcp_cli.py health
python scripts/mcp_cli.py whoami                       # Current token identity
python scripts/mcp_cli.py about
python scripts/mcp_cli.py space list
python scripts/mcp_cli.py space create my-project --rules-file rules.md
python scripts/mcp_cli.py live note my-project observation "Build OK"
python scripts/mcp_cli.py bank consolidate my-project
python scripts/mcp_cli.py bank read-all my-project
python scripts/mcp_cli.py token create agent-cline read,write
python scripts/mcp_cli.py graph connect my-project URL TOKEN MEM-ID -o general
python scripts/mcp_cli.py graph push my-project
python scripts/mcp_cli.py graph status my-project
python scripts/mcp_cli.py graph disconnect my-project

Interactive Shell

python scripts/mcp_cli.py shell

Autocomplete, history, Rich display. See scripts/README.md for full reference.


🧪 Tests

Unified test script with 4 selectable suites via --suite:

docker compose up -d   # Prerequisite

# All suites (44 tests, ~60s)
python scripts/test_recette.py --url http://localhost:8080

# Single suite
python scripts/test_recette.py --suite recette     # Agent pipeline (7 tests)
python scripts/test_recette.py --suite isolation    # Multi-tenant (18 tests)
python scripts/test_recette.py --suite qualite      # MCP tools (19 tests)

# Graph Memory suite (optional, requires running graph-memory)
python scripts/test_recette.py --suite graph \
  --graph-url http://host.docker.internal:8080 \
  --graph-token your_token

# List available suites
python scripts/test_recette.py --list

# Step-by-step + verbose
python scripts/test_recette.py --suite isolation -v --step --no-cleanup
Suite Tests Description
recette 7 Full pipeline: token → notes → LLM consolidation → bank
isolation 18 Multi-tenant isolation v0.7.1: cross-space access, backup filtering, auto-add token
qualite 19 MCP tools regression testing: system, admin, space, live, bank, backup, GC
graph ~8 Graph Memory bridge: connect, push, status, disconnect (optional)

🔒 Security

Authentication

  • Bearer Token mandatory on all MCP requests
  • Bootstrap key to create the first admin token
  • SHA-256 Tokens stored on S3 (never in clear text)
  • 3 levels: read, write, admin
  • Space scope: a token can be limited to specific spaces

WAF (Caddy + Coraza)

  • OWASP CRS: SQL/XSS injection, path traversal, SSRF
  • Rate Limiting: 200 MCP/min (Streamable HTTP)
  • Automatic TLS: Let's Encrypt in production (SITE_ADDRESS=domain.com)
  • Non-root container: mcp user

📂 Project Structure

live-memory/
├── src/live_mem/              # Source code (43 MCP tools + web interface)
│   ├── server.py              # FastMCP server + middlewares
│   ├── config.py              # pydantic-settings configuration
│   ├── auth/                  # Authentication
│   │   ├── middleware.py      #   Auth + Logging + StaticFiles
│   │   └── context.py         #   check_access, check_write, check_admin
│   ├── static/                # /live web interface
│   │   ├── live.html          #   SPA (Dashboard + Live + Bank)
│   │   ├── css/live.css       #   Styles (Cloud Temple theme)
│   │   ├── js/                #   7 JS modules (config, api, app, dashboard, timeline, bank, sidebar)
│   │   └── img/               #   Cloud Temple SVG Logo
│   ├── core/                  # Business services
│   │   ├── storage.py         #   S3 dual SigV2/SigV4 (Dell ECS)
│   │   ├── space.py           #   Memory spaces CRUD
│   │   ├── live.py            #   Live notes (append-only)
│   │   ├── consolidator.py    #   LLM Pipeline (4 steps)
│   │   ├── graph_bridge.py    #   🌉 Link to Graph Memory
│   │   ├── tokens.py          #   SHA-256 tokens management
│   │   ├── backup.py          #   S3 snapshots
│   │   ├── gc.py              #   Garbage Collector
│   │   ├── locks.py           #   asyncio locks per space
│   │   └── models.py          #   Pydantic models
│   └── tools/                 # MCP Tools (7 modules)
│       ├── system.py          #   3 tools (health, whoami, about)
│       ├── space.py           #   9 tools (spaces CRUD)
│       ├── live.py            #   3 tools (notes)
│       ├── bank.py            #   11 tools (bank + consolidation + supervision + maintenance)
│       ├── graph.py           #   4 tools (Graph Bridge)
│       ├── backup.py          #   5 tools (snapshots)
│       └── admin.py           #   8 tools (tokens + GC + purge + bulk)
├── scripts/                   # CLI + Shell + Tests
├── waf/                       # Caddy + Coraza WAF
├── WORKSPACE_CLINE_RULES.md           # 📋 Cline Custom Instructions template — Live Memory only
├── WORKSPACE_CLINE_ADVANCE_RULES.md   # 📋 Cline Custom Instructions template — Live Memory + Graph Memory
├── DESIGN/live-mem/           # 9 architecture documents
├── docker-compose.yml
├── Dockerfile
├── pyproject.toml             # Dependencies & project config (uv)
├── uv.lock                    # uv lockfile
├── VERSION                    # 2.5.1
├── CHANGELOG.md
└── FAQ.md

🔍 Troubleshooting

Service does not start

docker compose logs live-mem-service --tail 50
docker compose logs waf --tail 20

401 Unauthorized

  • Check your token: Authorization: Bearer YOUR_TOKEN
  • Bootstrap key is not a token — create a token first via admin_create_token

Consolidation fails

  • Check LLMaaS credentials in .env
  • Default timeout is 600s — increase CONSOLIDATION_TIMEOUT if needed
  • bank_consolidate returns an async job acknowledgement (running or queued) with next_action="return_to_user_without_polling"; call it once and do not watch/poll unless explicitly requested
  • bank_consolidation_status(job_id) remains available for manual status checks only

🤝 Contributing

Development is driven entirely through GitHub — issues, branches, pull requests, code reviews and project status all live there. This makes the project easy to pilot remotely from the command line with the gh CLI (including by AI coding agents): create an issue, branch, open a PR, review and merge without ever leaving the terminal or the GitHub UI.

The full, mandatory workflow is documented in WORKSPACE_WORKFLOW_GIT.md:

  • Branch + PR only — no local merge into main; every change lands through a pull request merged on GitHub.
  • Issue lifecycle — self-assign, move the Projects status to In Progress, keep solution-design discussion in the issue.
  • PR ↔ issue link — a Closes #N keyword in the PR body auto-closes the issue on merge.
  • PR-channel reviews — once a PR is open, code-review discussion moves to the PR; every review conclusion is published on GitHub (gh pr review / gh pr comment), not only in chat.

Following this file keeps the issue and PR histories clean and auditable, and lets a contributor (or an agent) drive the whole cycle reproducibly via gh.


🔗 Related Projects

Project Description Link
graph-memory Long-term memory (Knowledge Graph + RAG) github.com/Cloud-Temple/graph-memory

📄 License

Apache License 2.0


👤 Author

Cloud Templecloud-temple.com

Developed by Christophe Lesur.


Live Memory v2.5.1 — Shared working memory for collaborative AI agents

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Live Memory MCP Server — Shared working memory for collaborative AI agents (Memory Bank as a Service)

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