FPMS — Focal Point Memory System

Your AI forgets everything between conversations. FPMS fixes that.

Not just memory — attention management. FPMS tracks your projects, detects stuck tasks, and loads the right context at the right time.

What You Get

• - Cross-conversation memory — Start Monday, continue Wednesday, review Friday
• Structured work tracking — Projects → Tasks → Subtasks with status lifecycle
• Proactive alerts — "Task X has been blocked for 3 days"
• Smart context loading — Only loads what fits your token budget
• GitHub sync — Issues auto-sync as FPMS nodes

How It's Different From Other Memory Tools

	Mem0/Zep	FPMS
Remembers conversations	Yes	Yes (via prompt rules)
Tracks tasks & projects

No | Yes | | Alerts you about stuck work | No | Yes (heartbeat) | | Manages token budget | No | Yes (L0/L1/L2) | | Parent-child task hierarchy | No | Yes | | GitHub integration | No | Yes |

Other tools remember what was said. FPMS manages what needs to be done.

Setup

1. Install

CODEBLOCK0

2. Add MCP server to openclaw.yaml

CODEBLOCK1

3. Restart OpenClaw

That's it. 18 tools are now available in your conversations.

Use Cases

Project tracking

CODEBLOCK2

Decision memory

CODEBLOCK3

Risk detection

CODEBLOCK4

Available Tools (18)

Tool	What it does
INLINECODE0	Load memory context (call at conversation start)
INLINECODE1

Scan for risks: blocked, stale, at-risk tasks | | create_node | Create a project/task/goal | | update_status | Change status (inbox/active/waiting/done/dropped) | | append_log | Record decisions, progress, links | | get_context_bundle | Get token-budgeted context payload | | search_nodes | Find tasks by status, parent, source | | get_node | Get full details of a work item | | shift_focus | Switch AI attention to a specific task | | expand_context | See parent, children, dependencies | | update_field | Update title, summary, deadline, etc. | | attach_node / detach_node | Move tasks in hierarchy | | add_dependency / remove_dependency | Manage task dependencies | | unarchive | Restore completed/dropped tasks | | set_persistent | Protect tasks from auto-archive | | get_assembly_trace | Debug context assembly |

Automatic Memory Rules

Follow these rules in EVERY conversation:

1. 1. Conversation start → Call bootstrap to load memory
2. User mentions a task/project/goal → INLINECODE19
3. User makes a decision → append_log to the relevant node
4. Task progresses → INLINECODE21
5. Before conversation ends → append_log key takeaways
6. Every ~10 min → heartbeat to check for risks

Requirements

• - Python 3.10+
• No external services — runs 100% locally on SQLite

Links

• - GitHub
• PyPI
• Full Documentation