coord-mem MCP Server

coord-mem MCP Server

Memory-palace graph MCP server for AI agent memory, exposing memory_add / get / like / record_window / walk / retrieve / neighbors / rooms / misshelved / rehome operations over a zero-dependency, append-only, provenance-tracking knowledge graph with decay, PMI-derived adjacency, and spatial coordinates.

Category
访问服务器

README

coord-mem

A memory-palace graph for AI agent memory — zero-dependency Node, with a CLI, an MCP server, and a live starfield renderer.

Memories are append-only nodes rooted at an origin. Each records:

  • Provenance — the context set: ids of every memory present when the thought formed. Multi-parent, captured at creation, immutable forever.
  • Placement — one chosen home (the shelf where you'd look for it), making the graph walkable as a tree from the origin. Mutable via rehome.
  • Coordinate — a stored (x, y, z) lattice address, auto-assigned to the nearest free slot beside its home. Stable, citable, never contested; moves only with rehome.

Two live signals grow on top:

  • Brightness — decayed warmth from use plus rare, heavily-weighted likes. Decides retrieval rank and render glow.
  • Adjacency — never declared; derived as PMI over recorded context windows ("these two memories appear together more than their popularity predicts"). Feeds neighbor queries, retrieval expansion, room clustering, and mis-shelving detection — a memory whose co-travelers live far from its shelf gets flagged with a suggested re-home.

Address vs. affinity is the core design split: the coordinate is where a memory lives; PMI is how it's used. Their disagreement is signal.

Everything decays (default half-life 30 days), the store is append-only (supersede, never delete), and the core is deterministic (injectable clock, no randomness). The full argument for every decision — including the non-goals — is in DESIGN.md.

Quickstart

npm test                      # zero deps, Node >= 22, built-in test runner

node bin/coord-mem.js init "My project's core principles"
node bin/coord-mem.js add "Decision X because Y" --tags decision
node bin/coord-mem.js add "Refinement of that" --home n1 --context n1
node bin/coord-mem.js walk
node bin/coord-mem.js retrieve decision

Store path via --file <path> or COORD_MEM_PATH (default ./coord-mem.json).

Starfield renderer

npm run view                  # http://localhost:4444

Self-contained canvas app, polls live. Palace mode pins each star at its stored coordinate — a stable map you can memorize. Gravity mode lets PMI springs pull co-used memories together — the usage clusters. Glow is brightness; cyan threads are co-occurrence; red rings are mis-shelved.

Claude Code integration

This repo dogfoods itself as live memory for agent sessions:

  • .mcp.json registers bin/mcp-server.js (hand-rolled stdio JSON-RPC, still zero-dep) exposing memory_add / get / like / record_window / walk / retrieve / neighbors / rooms / misshelved / rehome.
  • A Stop hook (bin/record-window-hook.js) scans each turn's transcript for memory tool activity and records one context window over every memory touched — so merely using memories maintains brightness and adjacency, hands-free.
  • CLAUDE.md instructs sessions to author memories routinely but selectively: store decisions-with-why, reversals, and hard-won constraints; never activity logs. The bar: would a cold future session act differently for having read this?

palace.json is this repo's own live palace — the project's design history, recorded as it happened.

Origin

The model began as a question: would a spatial, origin-rooted social graph (posts as stars, tips as brightness) work as agent memory? What survived the design argument: append-only permanence, origin-rooted traceability, use-driven brightness, stored addresses. What didn't: typed faces, contested coordinates, single-parent provenance, deletion. See DESIGN.md.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选