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.
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.jsonregistersbin/mcp-server.js(hand-rolled stdio JSON-RPC, still zero-dep) exposingmemory_add / get / like / record_window / walk / retrieve / neighbors / rooms / misshelved / rehome.- A
Stophook (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.mdinstructs 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.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
E2B
Using MCP to run code via e2b.