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Memory MCP

核心功能涵盖跨会话记忆存储检索、知识图谱实体关系管理、用户 persona/情绪追踪、项目任务管理、短期KV存储、记忆共享等,通过9个工具的丰富操作实现。典型场景包括跨会话协作、用户行为分析、项目跟进等。需依赖memory MCP服务器,输入为含userId、op等参数的JSON请求,输出对应操作结果,还支持8阶段自动关联记忆、智能建议等特性。

cyber-bye
cyber-bye
热度 25.67
最近更新 2026-06-09 11:34:53
分类:知识依赖:MCP 服务应用场景:笔记整理 / 任务管理 / 研究 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add memory-mcp-cyber-bye
Metadata
name
memory-mcp-cyber-bye
description
Graph-based memory MCP server with 9 consolidated tools, 8-phase auto-linking, persona tracking, emotional memory, adaptive learning, and knowledge graph entities.
version
1.0.7
metadata
{"openclaw":{"emoji":"🧠","requires":{"bins":["node"],"mcp":["memory__memory","memory__entity","memory__relation","memory__short_term","memory__project","memory__context","memory__extract","memory__share","memory__memory_tool_search"]}}}

Memory MCP — Graph-Based Memory & Persona Management

[!IMPORTANT] Dependency Warning: This skill requires the memory MCP server to be running and registered with the Model Context Protocol (MCP) host. It enables persistent memory, knowledge graph entities, context tracking, and cross-session intelligence.

This skill equips the agent to store, search, and manage memories across sessions; track entities and relationships in a knowledge graph; maintain user persona, mood, and learning patterns; and surface proactive suggestions based on memory health.


Guidelines for the Agent

1. Tool Architecture — 9 Consolidated Tools

The memory MCP exposes 9 tools, each with an op (operation) parameter:

Tool Prefix Purpose Operations
memory__memory memory_ Core memory store & search remember, recall, search, context, stats, health, decay, boost, pin, inspect, export, import, trim, suggest, remind, dedup, backup, restore, snippet_search, contact, contact_graph
memory__entity entity_ Knowledge graph entities create, read, update, delete, search
memory__relation relation_ Entity relationships create, delete, search
memory__short_term short_term_ Fast KV storage set, get, list, delete, clear, search
memory__project project_ Projects, tasks, workflows create_project, get_project, list_projects, update_project, delete_project, plan_task, get_task, list_tasks, update_task, complete_task, delete_task, plan_workflow, get_workflow, list_workflows
memory__context context_ Conversation context better, chat_add, chat_get, chat_summary, get_summary
memory__extract extract_ Extract/remember info entities, text, keypoint, thought, note, discovery, mistake, learning, boundary
memory__share share_ Share with others share, shared_with_me, shared_by_me, get_network, person_memories
memory__memory_tool_search — Find tools by keyword query

2. Common Parameters

Every tool call requires:

  • userId (required) — Who owns this data. Always pass the user identifier.
  • op (required) — Which operation to perform on the tool.

Each tool also accepts optional context parameters:

  • projectId — Scope to a project
  • sessionId — Conversation thread identifier

3. Core Memory Operations (memory__memory)

Store a Memory

{ "op": "remember", "userId": "u1", "userMessage": "Fixed @AuthService bug!", "agentMessage": "Great work!" }

Auto-features: intent detection, entity extraction (@mentions, CamelCase, URLs), auto-linking.

Search / Recall

{ "op": "recall", "userId": "u1", "query": "auth bug" }
{ "op": "search", "userId": "u1", "query": "database config" }

Context for LLM

{ "op": "context", "userId": "u1", "sessionId": "sess_123", "maxTokens": 2000 }

Memory Health & Maintenance

{ "op": "health", "userId": "u1" }
{ "op": "decay", "userId": "u1", "daysUnused": 7 }
{ "op": "dedup", "userId": "u1", "threshold": 0.8, "autoMerge": false }

Smart Features

{ "op": "suggest", "userId": "u1" }
{ "op": "remind", "userId": "u1", "reminderType": "followup", "title": "Check database", "priority": 8 }
{ "op": "mood", "userId": "u1", "mood": "excited", "intensity": 8, "context": "Launch day!" }
{ "op": "persona", "userId": "u1", "traits": {"creative": true}, "style": "friendly" }
{ "op": "learn", "userId": "u1", "type": "work", "pattern": "prefers morning" }

Snippet Search (Exact & Semantic with context)

{
  "op": "snippet_search",
  "userId": "u1",
  "text": "Line 1: system boot\nLine 2: loading config...",
  "query": "system boot",
  "searchType": "exact",
  "beforeLimit": 1,
  "afterLimit": 1
}

Supports exact/semantic matches, parameter clamping, whitespace collapsing, and SQL wildcard escaping in database fallback.

Unified Contact CRUD

{ "op": "contact", "contactOp": "create", "userId": "u1", "name": "vk", "role": "founder", "properties": {"status": "active"} }
{ "op": "contact", "contactOp": "get", "userId": "u1", "name": "VK" }

Standardizes contact management with space-collapsed names, case-insensitive retrievals, and properties sanitization.

Unified Contact Graph & Path Traversal

{ "op": "contact_graph", "graphOp": "link", "userId": "u1", "fromId": "vk", "toId": "nandini", "relationType": "wife" }
{ "op": "contact_graph", "graphOp": "path", "userId": "u1", "fromId": "vk", "toId": "vk", "depth": 3 }

Manages relationships with lowercase-normalized edge types, per-path visited tracking, and loop/cycle discovery.


4. Knowledge Graph (entity + relation)

Create Entity

{ "op": "create", "userId": "u1", "entityType": "Person", "name": "Alice", "properties": {"role": "Engineer"} }

Search Entities

{ "op": "search", "userId": "u1", "entityType": "Person", "search": "alice" }

Create Relation

{ "op": "create", "userId": "u1", "fromId": "e1", "toId": "e2", "type": "WORKS_WITH" }

5. Short-Term KV Storage (memory__short_term)

Fast key-value store for session data. Cleared periodically.

{ "op": "set", "userId": "u1", "key": "active_task", "value": {"id": "t1"} }
{ "op": "get", "userId": "u1", "key": "active_task" }
{ "op": "list", "userId": "u1" }

6. Project & Task Management (memory__project)

{ "op": "create_project", "userId": "u1", "name": "My App", "description": "A new app" }
{ "op": "plan_task", "userId": "u1", "projectId": "p1", "title": "Fix bug", "status": "pending" }
{ "op": "list_tasks", "userId": "u1", "projectId": "p1" }
{ "op": "complete_task", "id": "task_123" }

7. Context Tracking (memory__context)

{ "op": "better", "userId": "u1", "timeRange": "week" }
{ "op": "chat_add", "userId": "u1", "role": "user", "content": "Hello" }
{ "op": "chat_get", "userId": "u1", "limit": 10 }

8. Extract & Remember (memory__extract)

{ "op": "entities", "userId": "u1", "text": "John from Acme called" }
{ "op": "learning", "userId": "u1", "insight": "Tests first" }
{ "op": "discovery", "userId": "u1", "content": "Found new approach" }
{ "op": "mistake", "userId": "u1", "description": "Used wrong API", "resolution": "Update docs" }

9. Share (memory__share)

{ "op": "share", "userId": "u1", "toOwnerId": "u2", "content": "Deadline Sunday" }
{ "op": "shared_with_me", "userId": "u1" }

10. 8-Phase Auto-Linking System

Memories are automatically linked across sessions using:

Phase Method Description
0 Temporal Same conversation flow (strongest)
1 Entity Shared @mentions, CamelCase entities
2 Project Same project context
3 Intent Same detected intent
4 Keyword Content keyword overlap
5 Cross-Project Related across different projects
6 Temporal Chain Within 30-minute window
7 Entity Graph Knowledge graph traversal

Features: bidirectional links, max 15 links per memory, adaptive boost for high-priority items.


11. Intent Detection (Auto)

The system auto-detects intent when storing memories:

Intent Priority Examples
error 80% bug, crash, failed
success 70% fixed, working, completed
learning 80% learned, discovered
question 50% how, why, what
planning 50% will, going to

12. Session Workflow

At session start:

// Get recent context
{ "op": "better", "userId": "u1", "timeRange": "week" }

// Check pending reminders
{ "op": "remind", "userId": "u1" }

// Get health overview
{ "op": "health", "userId": "u1" }

During session:

// Store conversation
{ "op": "remember", "userId": "u1", "userMessage": "...", "agentMessage": "..." }

// Extract entities
{ "op": "entities", "userId": "u1", "text": "..." }

// Track mood
{ "op": "mood", "userId": "u1", "mood": "happy", "context": "..." }

At session end:

// Store summary
{ "op": "chat_summary", "userId": "u1", "summary": "..." }

// Clean up short-term
{ "op": "cleanup", "userId": "u1" }

13. Error Handling

Error Cause Solution
"id required" Missing ID param Add id field
"sessionId required" Missing sessionId Add sessionId field
"mood required" Missing mood Add mood (happy/sad/excited/etc)
"userId required" Missing userId Always pass userId

14. Best Practices

  1. Always pass userId — Every tool call requires it.
  2. Use entity extraction — Extract entities from user messages to build the knowledge graph.
  3. Track mood — Call mood during emotionally significant moments.
  4. Remember at end — Store session summaries for cross-session continuity.
  5. Use context before starting — better op gives you full context before you begin.
  6. Health check periodically — Run health + decay to keep memory clean.