userType: external

gitBranch: claude/intelligent-yalow

slug: swift-imagining-prism

type: progress

hookEvent: SessionStart

command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/boot_context_inject.py


command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/capability_audit.py


command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/memory_context_inject.py


command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/session_recovery_start.py


command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/session_sync.py


command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/sunaiva_session_inject.py


type: user

role: user

content:
Your task is to create a detailed summary of the conversation so far, paying close attention to the user's explicit requests and your previous actions.
This summary should be thorough in capturing technical details, code patterns, and architectural decisions that would be essential for continuing development work without losing context.

Before providing your final summary, wrap your analysis in <analysis> tags to organize your thoughts and ensure you've covered all necessary points. In your analysis process:

1. Chronologically analyze each message and section of the conversation. For each section thoroughly identify:
   - The user's explicit requests and intents
   - Your approach to addressing the user's requests
   - Key decisions, technical concepts and code patterns
   - Specific details like:
     - file names
     - full code snippets
     - function signatures
     - file edits
  - Errors that you ran into and how you fixed them
  - Pay special attention to specific user feedback that you received, especially if the user told you to do something differently.
2. Double-check for technical accuracy and completeness, addressing each required element thoroughly.

Your summary should include the following sections:

1. Primary Request and Intent: Capture all of the user's explicit requests and intents in detail
2. Key Technical Concepts: List all important technical concepts, technologies, and frameworks discussed.
3. Files and Code Sections: Enumerate specific files and code sections examined, modified, or created. Pay special attention to the most recent messages and include full code snippets where applicable and include a summary of why this file read or edit is important.
4. Errors and fixes: List all errors that you ran into, and how you fixed them. Pay special attention to specific user feedback that you received, especially if the user told you to do something differently.
5. Problem Solving: Document problems solved and any ongoing troubleshooting efforts.
6. All user messages: List ALL user messages that are not tool results. These are critical for understanding the users' feedback and changing intent.
6. Pending Tasks: Outline any pending tasks that you have explicitly been asked to work on.
7. Current Work: Describe in detail precisely what was being worked on immediately before this summary request, paying special attention to the most recent messages from both user and assistant. Include file names and code snippets where applicable.
8. Optional Next Step: List the next step that you will take that is related to the most recent work you were doing. IMPORTANT: ensure that this step is DIRECTLY in line with the user's most recent explicit requests, and the task you were working on immediately before this summary request. If your last task was concluded, then only list next steps if they are explicitly in line with the users request. Do not start on tangential requests or really old requests that were already completed without confirming with the user first.
                       If there is a next step, include direct quotes from the most recent conversation showing exactly what task you were working on and where you left off. This should be verbatim to ensure there's no drift in task interpretation.

Here's an example of how your output should be structured:

<example>
<analysis>
[Your thought process, ensuring all points are covered thoroughly and accurately]
</analysis>

<summary>
1. Primary Request and Intent:
   [Detailed description]

2. Key Technical Concepts:
   - [Concept 1]
   - [Concept 2]
   - [...]

3. Files and Code Sections:
   - [File Name 1]
      - [Summary of why this file is important]
      - [Summary of the changes made to this file, if any]
      - [Important Code Snippet]
   - [File Name 2]
      - [Important Code Snippet]
   - [...]

4. Errors and fixes:
    - [Detailed description of error 1]:
      - [How you fixed the error]
      - [User feedback on the error if any]
    - [...]

5. Problem Solving:
   [Description of solved problems and ongoing troubleshooting]

6. All user messages:
    - [Detailed non tool use user message]
    - [...]

7. Pending Tasks:
   - [Task 1]
   - [Task 2]
   - [...]

8. Current Work:
   [Precise description of current work]

9. Optional Next Step:
   [Optional Next step to take]

</summary>
</example>

Please provide your summary based on the conversation so far, following this structure and ensuring precision and thoroughness in your response.

There may be additional summarization instructions provided in the included context. If so, remember to follow these instructions when creating the above summary. Examples of instructions include:
<example>
## Compact Instructions
When summarizing the conversation focus on typescript code changes and also remember the mistakes you made and how you fixed them.
</example>

<example>
# Summary instructions
When you are using compact - please focus on test output and code changes. Include file reads verbatim.
</example>

Additional Instructions:
{}

IMPORTANT: Do NOT use any tools. You MUST respond with ONLY the <summary>...</summary> block as your text output.


type: message

role: assistant

type: text

text:
<analysis>
Let me carefully analyze the conversation from this session to create a comprehensive summary.

## Session Context
This session resumed after compaction. The pre-compaction summary established:
- GENESIS_PERPETUAL_SWARM_MASTER_PRD.md was written (777 lines, completed)
- PRD was updated with real Elestio service names and specs
- BrowserlessConfig + FalkorDBConfig + GraphitiConfig were added to both elestio_config.py files
- browserless_qa_army.py was written (~470 lines)
- The user's directive was "utilise elestio browserless as required"

## This Session's Events

### 1. Session Resume
- Claude updated the todo list to mark completed items and set "Get Browserless TOKEN from Elestio dashboard and wire into secrets.env" as in_progress
- Started to navigate to Elestio dashboard to get the Browserless TOKEN

### 2. User Interrupt - New Question
The user sent a new message asking about the sunaiva-memory service:
"is the sunaiva-memory service correctly hooked up as the sunaiva memory mcp homebase for private memory instances, one for each customer? show me the memory mcp visual map design now. use excalidraw skill"

### 3. Investigation Phase
Claude pivoted to investigate:
- Launched Explore agent to audit sunaiva-memory service connections (background agent a0bac81)
- Read `.claude/settings.json` - found sunaiva-memory MCP registered as `python3 /mnt/e/genesis-system/Sunaiva/ai-memory/mcp/server.py --transport stdio --vault-id 41f4785c-e9e0-43ac-b6e8-eedb571fba57`
- Listed mcp-servers directory to understand the full landscape
- Listed Sunaiva/ai-memory directory structure (comprehensive listing found)
- Read server.py (454 lines) - Multi-user MCP server with vault_id routing, 6 MCP tools
- Read vault_loader.py (746 lines) - PostgreSQL primary + JSON fallback, sunaiva schema
- Read mcp/ARCHITECTURE.md (442 lines) - Full architecture documentation
- Read server/mcp_generator.py (321 lines) - Per-user server generation template
- Read server/database.py (676 lines) - Full PostgreSQL schema, ThreadedConnectionPool, sunaiva schema

### 4. Key Findings
Claude determined:
- sunaiva-memory Elestio service = CI/CD deploy server for the API + MCP code (NOT a database)
- MCP registered in Claude settings with single hardcoded vault-id (Kinan's vault only)
- vault_loader.py: PostgreSQL primary, JSON fallback, sunaiva schema
- Architecture correctly supports per-customer isolation via vault_id UUID routing
- NOT deployed to production SSE mode yet (memory.sunaiva.ai doesn't resolve)
- 5 gaps identified: DNS, env vars, George's vault, Qdrant wiring, API key auth

### 5. Excalidraw File Creation
- Created directory E:\genesis-system\docs\diagrams\ (didn't exist)
- Wrote E:\genesis-system\docs\diagrams\sunaiva_memory_mcp_map.excalidraw (725 lines)
- Comprehensive Excalidraw JSON with 5 layers, color-coded boxes, full architecture

### Files Examined:
1. E:\genesis-system\.claude\settings.json - MCP server registrations
2. E:\genesis-system\Sunaiva\ai-memory\mcp\server.py - 454 lines, MCP server
3. E:\genesis-system\Sunaiva\ai-memory\mcp\vault_loader.py - 746 lines, storage layer
4. E:\genesis-system\Sunaiva\ai-memory\mcp\ARCHITECTURE.md - 442 lines, docs
5. E:\genesis-system\Sunaiva\ai-memory\server\mcp_generator.py - 321 lines
6. E:\genesis-system\Sunaiva\ai-memory\server\database.py - 676 lines, full schema

### Files Created:
1. E:\genesis-system\docs\diagrams\sunaiva_memory_mcp_map.excalidraw - 725 lines

The summary was requested immediately after writing the Excalidraw file - the file was written successfully.

The todo list at end of session:
- ✅ Write GENESIS_PERPETUAL_SWARM_MASTER_PRD.md
- ✅ Update PRD with real Elestio service names and specs
- ✅ Add BrowserlessConfig + FalkorDBConfig + GraphitiConfig to elestio_config.py
- ✅ Write browserless_qa_army.py integration script
- 🔄 Build Sunaiva Memory MCP Excalidraw visual map (just completed)
- ⏳ Get Browserless TOKEN (deprioritized when user changed topic)

The Excalidraw file was just completed when the summary was requested.
</analysis>

<summary>
1. Primary Request and Intent:

This session resumed mid-task from compaction. Two work streams were active:

**Carried over from pre-compaction:**
- Directive: "utilise elestio browserless as required" — integrate Elestio Browserless as Browser QA Army backbone
- Completed: GENESIS_PERPETUAL_SWARM_MASTER_PRD.md updated, browserless_qa_army.py written, BrowserlessConfig/FalkorDBConfig/GraphitiConfig added to elestio_config.py files
- Pending: Get BROWSERLESS_TOKEN from Elestio dashboard and wire into secrets.env

**New user request (interrupt):**
"is the sunaiva-memory service correctly hooked up as the sunaiva memory mcp homebase for private memory instances, one for each customer? show me the memory mcp visual map design now. use excalidraw skill"

Intent: Understand if the Elestio `sunaiva-memory` service is properly architected for per-customer private memory vaults via MCP, and produce an Excalidraw visual map of the entire architecture.

2. Key Technical Concepts:
- **Sunaiva MCP Server**: FastMCP-based server (`server.py`) serving personalized memory vaults via vault_id routing — stdio for local (Kinan), SSE for remote customers
- **Vault ID isolation**: Each customer gets a UUID `vault_id`; ALL PostgreSQL queries are scoped by `vault_id` FK — zero cross-customer data leakage
- **vault_loader.py dual-mode**: PostgreSQL (Elestio `postgresql-genesis`, `sunaiva` schema) PRIMARY, JSON file fallback on disk
- **sunaiva schema**: 8 tables — `users`, `vaults`, `vault_entities`, `vault_decisions`, `vault_preferences`, `vault_conversations`, `api_keys`, `usage_events`
- **ThreadedConnectionPool**: psycopg2 pool (2-10 connections), TCP keepalives for Elestio idle SSL timeout prevention
- **sunaiva-memory Elestio service**: CI/CD deploy service (not a DB) — hosts the API server + MCP server.py; labeled "CI/CD" in Elestio dashboard
- **MCP tools (6)**: `recall(query)`, `who_am_i()`, `my_decisions(topic)`, `my_entities(type)`, `my_style()`, `remember(fact)`
- **stdio vs SSE transport**: Kinan uses stdio with `--vault-id` flag; customers use SSE at `memory.sunaiva.ai/mcp/?vault_id=UUID`
- **Excalidraw JSON format**: Native Excalidraw `.excalidraw` format with elements array (rectangles, text, arrows), appState, color-coded layers
- **Per-customer vault provisioning flow**: signup → ingest → store in PG → receive MCP URL → agent knows customer instantly
- **Production gaps identified**: DNS not set, SUNAIVA_DB_* env vars not set on Elestio, George's vault not provisioned, Qdrant not wired into recall(), API key auth not enforced

3. Files and Code Sections:

- **`E:\genesis-system\.claude\settings.json`** (READ — not modified)
  - Critical: Shows all registered MCP servers. Found sunaiva-memory registration:
  ```
  sunaiva-memory: python3 /mnt/e/genesis-system/Sunaiva/ai-memory/mcp/server.py --transport stdio --vault-id 41f4785c-e9e0-43ac-b6e8-eedb571fba57
  ```
  - Key finding: Single hardcoded vault-id = Kinan's vault only. No per-customer routing in current Claude registration.

- **`E:\genesis-system\Sunaiva\ai-memory\mcp\server.py`** (READ — 454 lines)
  - FastMCP server with 6 tools + 4 resources
  - Vault context pattern:
  ```python
  _current_vault_id: Optional[str] = None
  def set_vault_context(vault_id: str) -> None:
      global _current_vault_id
      _current_vault_id = vault_id
  def get_vault_context() -> str:
      if _current_vault_id is None:
          raise ValueError("No vault_id in context")
      return _current_vault_id
  ```
  - stdio mode requires `--vault-id` arg; SSE mode expects `?vault_id=` query param
  - Production SSE URL pattern: `https://memory.sunaiva.ai/mcp/?vault_id=YOUR_VAULT_ID`

- **`E:\genesis-system\Sunaiva\ai-memory\mcp\vault_loader.py`** (READ — 746 lines)
  - Dual-mode storage: PostgreSQL primary, JSON file fallback
  - DB config pattern:
  ```python
  DB_HOST = os.environ.get("SUNAIVA_DB_HOST", "")
  DB_PORT = int(os.environ.get("SUNAIVA_DB_PORT", "0") or "0")
  DB_USER = os.environ.get("SUNAIVA_DB_USER", "")
  DB_PASSWORD = os.environ.get("SUNAIVA_DB_PASSWORD", "")
  DB_NAME = os.environ.get("SUNAIVA_DB_NAME", "")
  DATABASE_URL = os.environ.get("DATABASE_URL", "")
  SCHEMA = "sunaiva"
  ```
  - Pool initialization with TCP keepalives:
  ```python
  _pool = ThreadedConnectionPool(
      POOL_MIN, POOL_MAX,
      keepalives=1, keepalives_idle=30,
      keepalives_interval=10, keepalives_count=5,
      connect_timeout=10,
  )
  ```
  - `load_vault(vault_id)` tries PostgreSQL first, falls back to JSON
  - Key: 30-second cooldown before retrying failed pool

- **`E:\genesis-system\Sunaiva\ai-memory\mcp\ARCHITECTURE.md`** (READ — 442 lines)
  - Documents Phase 1 (current MVP: JSON files, keyword search), Phase 2 (Qdrant vectors), Phase 3 (global edge)
  - Confirmed production URL intent: `https://memory.sunaiva.ai`
  - Performance target: 10-50ms recall latency

- **`E:\genesis-system\Sunaiva\ai-memory\server\database.py`** (READ — 676 lines)
  - Full sunaiva schema SQL:
  ```sql
  CREATE SCHEMA IF NOT EXISTS sunaiva;
  CREATE TABLE IF NOT EXISTS users (id UUID PRIMARY KEY DEFAULT gen_random_uuid(), email TEXT UNIQUE NOT NULL, password_hash TEXT NOT NULL, name TEXT NOT NULL DEFAULT 'User', plan_tier TEXT NOT NULL DEFAULT 'free', ...);
  CREATE TABLE IF NOT EXISTS vaults (id UUID PRIMARY KEY DEFAULT gen_random_uuid(), user_id UUID NOT NULL REFERENCES sunaiva.users(id) ON DELETE CASCADE, ...);
  CREATE TABLE IF NOT EXISTS vault_entities (vault_id UUID NOT NULL REFERENCES sunaiva.vaults(id) ON DELETE CASCADE, name TEXT, type TEXT, context JSONB, mentions INT, ...);
  CREATE TABLE IF NOT EXISTS vault_decisions (vault_id UUID FK, decision TEXT, context TEXT, date TEXT, importance REAL);
  CREATE TABLE IF NOT EXISTS vault_preferences (vault_id UUID FK, category TEXT, preference JSONB);
  CREATE TABLE IF NOT EXISTS vault_conversations (vault_id UUID FK, source_platform TEXT, message_count INT, raw_data JSONB);
  CREATE TABLE IF NOT EXISTS api_keys (vault_id UUID FK, key_hash TEXT);
  CREATE TABLE IF NOT EXISTS usage_events (user_id UUID FK, event_type TEXT, metadata JSONB);
  ```
  - Self-healing connection pool: liveness check `SELECT 1` before each use, pool recreation on stale connections

- **`E:\genesis-system\Sunaiva\ai-memory\server\mcp_generator.py`** (READ — 321 lines)
  - Template-based per-user MCP server generation (legacy approach, superseded by multi-tenant server.py)
  - `generate_mcp_server(knowledge_path, output_path, user_name, vault_id)` generates standalone server per customer

- **`E:\genesis-system\docs\diagrams\sunaiva_memory_mcp_map.excalidraw`** (CREATED — 725 lines)
  - Full Excalidraw JSON visual map with 5 layers:
    - Layer 1: AI Agent Clients (Claude Code/Kinan, George's Agent, Customer #2+, AIVA, any MCP client)
    - Layer 2: Sunaiva MCP Server (tools box, vault ID router, live status)
    - Layer 3: Vault Loader (PostgreSQL primary, JSON fallback)
    - Layer 4: Elestio Infrastructure (all 6 services: sunaiva-memory, postgresql-genesis, redis-genesis, qdrant-b3knu, n8n-genesis, browserless-genesis)
    - Layer 5: Per-Customer Onboarding Flow (5 steps: signup → ingest → store → MCP URL → AI knows them)
    - Gaps section + working status banner
  - Color coding: blue=Genesis/PostgreSQL, green=George/working, purple=AIVA/sunaiva-memory, red=c92a2a/Redis, orange=Browserless, gray=future

4. Errors and Fixes:
- **Directory creation error**: First attempt to write Excalidraw file failed with `ENOENT: no such file or directory` because `E:\genesis-system\docs\diagrams\` didn't exist. Fixed by calling `mcp__Desktop_Commander__create_directory` first, then re-writing the file successfully.

5. Problem Solving:
- **Is sunaiva-memory correctly hooked up?** Answer: PARTIALLY. Architecture is correct (vault_id isolation, PostgreSQL sunaiva schema), but 5 gaps prevent production per-customer mode:
  1. DNS: `memory.sunaiva.ai` not pointing to Elestio sunaiva-memory service
  2. Env vars: `SUNAIVA_DB_HOST/PORT/USER/PASS/DB_NAME` not set on Elestio sunaiva-memory service (so vault_loader falls back to JSON files)
  3. George's vault: not provisioned in PostgreSQL (no row in `sunaiva.vaults` for George)
  4. Qdrant: `recall()` uses keyword search, not semantic vector search (Phase 2)
  5. API key auth: `api_keys` table exists but MCP endpoint not enforcing it

6. All User Messages:
- "is the sunaiva-memory service correctly hooked up as the sunaiva memory mcp homebase for private memory instances, one for each customer? show me the memory mcp visual map design now. use excalidraw skill"

(Pre-compaction messages carried over as context):
- "we have elestio browserless service yes we do and we have falkor db and graphiti too"
- [Elestio dashboard screenshot/text listing 6 running services]

7. Pending Tasks:
- **Get Browserless TOKEN from Elestio dashboard** — navigate to `browserless-genesis` → Env Vars → copy TOKEN → add to `config/secrets.env` as `BROWSERLESS_TOKEN=...` (was in_progress before user interrupt)
- **Run Browserless connection test**: `python scripts/browserless_qa_army.py --test-connection`
- **Wire FalkorDB credentials** — service confirmed live but config dataclass has placeholder host
- **Wire Graphiti credentials** — same pattern as FalkorDB
- **Fix PRD architecture diagram** — ASCII art box still shows old "BROWSER ARMY (Playwright)" text (edit_block failed twice)
- **Deploy sunaiva-memory to SSE mode** — DNS + SUNAIVA_DB_* env vars + SSE server deployment for per-customer mode
- **Provision George's vault** — call `/api/register` for George, upload his conversation history
- **Add SUNAIVA_DB_* env vars** to Elestio sunaiva-memory service so PostgreSQL is primary (not JSON fallback)

8. Current Work:
Immediately before this summary, Claude had just successfully written the Excalidraw visual map to `E:\genesis-system\docs\diagrams\sunaiva_memory_mcp_map.excalidraw` (725 lines). The file required first creating the `docs\diagrams\` directory (which didn't exist), then writing the complete Excalidraw JSON.

The map covers 5 architectural layers with color-coded components, a per-customer onboarding flow (5 steps), a gap analysis section, and a working status banner. It documents that Kinan's vault is live via stdio but production SSE per-customer mode has 5 gaps to close.

The background Explore agent (a0bac81) was still running when the summary was requested, auditing the sunaiva-memory connections.

9. Optional Next Step:
The Excalidraw map was just completed. The user's request was: "show me the memory mcp visual map design now. use excalidraw skill"

The map has been written to `E:\genesis-system\docs\diagrams\sunaiva_memory_mcp_map.excalidraw`. The next step is to present the findings to the user — specifically:
1. Confirm the Excalidraw file is written and provide the path
2. Answer the user's question directly: "is the sunaiva-memory service correctly hooked up?" (Answer: Partially — architecture is correct but 5 gaps prevent production per-customer mode)
3. Offer to open the Excalidraw file in the browser at excalidraw.com, or proceed to close the gaps (most impactful: set SUNAIVA_DB_* env vars on Elestio + provision George's vault)
</summary>

service_tier: standard

type: assistant


hookEvent: SubagentStop

hookName: SubagentStop

command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/observability_logger.py --event subagent_stop