Link

AI 에이전트를 위한 로컬 마크다운 메모리

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Link

Link

Local memory for AI agents.

Link gives Codex, Claude, Cursor, Kiro, VS Code, Copilot, Antigravity, and other local agents the same source-backed memory, stored locally as Markdown.

Website · How it works · Memory · Tools & CLI · Setup · Docs · MCP Registry · PyPI · Homebrew

GitHub stars CI MCP Registry PyPI

Link — local, source-backed memory for AI agents

What Is Link?

Link is an open-source memory layer for local AI agents. Raw sources become an inspectable Markdown wiki. Explicit "remember this" requests become reviewable memories. Agents retrieve compact, source-backed context through the CLI, MCP, official skills, or the local viewer without dumping the whole wiki into a chat window.

The wiki is the storage layer. The product is durable memory that stays on your machine, remains readable in plain files, and can be shared across multiple agents instead of locked inside one vendor profile.

How It Works

Link gives agents four simple moves:

  1. Capture notes, transcripts, docs, screenshots, and project context in raw/.
  2. Structure source-backed pages under wiki/.
  3. Remember explicit preferences, decisions, facts, and project context as reviewable memory.
  4. Retrieve compact query packets through the CLI, MCP, official skills, or the local web viewer.

Most agent sessions start from zero. You re-explain preferences, repo decisions, project constraints, and why something matters. Link turns that repeated context into local memory agents can query.

PainLink's answer
Agents forget you between sessions.Save reviewed preferences, decisions, facts, and project context.
Notes are private or messy.Keep raw sources local, then turn them into source-backed Markdown.
Context windows are expensive.Return compact query packets with provenance and follow-up actions.
Memory needs trust.Every page and memory can be inspected, reviewed, archived, or forgotten.

Link follows Andrej Karpathy's LLM Wiki pattern: keep knowledge outside the chat window, make claims inspectable, and let context compound over time.

Quick Start

Start with the memory proof. It creates a clean local workspace, writes one reviewed memory, and proves that the same memory can be recalled through CLI, official skills, and MCP. No web server is required for the proof.

brew install gowtham0992/link/link
lnk proof

The installed command is lnk because link is already a POSIX/macOS system utility. From a source checkout, use python3 link.py ... instead.

You should see:

Cross-agent memory continuity works
Memory: created and reviewed: Cross-agent Link proof
Recall: found through the same bounded recall path used by CLI, skills, and MCP.
Result: proof passed

That is the core promise: one local memory, reusable by different agents, without a hidden cloud profile.

Then run the richer demo when you want the UI, graph, source pages, and query packets:

lnk try
lnk serve link-demo

lnk try creates the demo, checks readiness, runs compact query/brief examples, and prints the first agent prompts. Windows, source checkout, MCP-only, and skill-first setup live in the First 10 Minutes guide.

When you are ready to use Link for real memory, run one guided command:

lnk onboard
lnk onboard --first-memory "I prefer concise release notes"
lnk onboard --seed-project .
lnk onboard --agent codex
lnk onboard --agent codex --write

lnk onboard creates or repairs ~/link, checks health, prints the exact agent prompts to try, and previews MCP wiring for Codex, Claude Code, Cursor, Kiro, VS Code, Copilot, Antigravity, and other supported clients. It only writes an agent config when you pass --write. Add --seed-project . from inside a repo when you want onboarding to create the first source-backed project context page.

Or seed your current repo as a separate step so the first real recall is not empty:

cd /path/to/your/project
lnk seed . ~/link
lnk query "what is this project about?" ~/link --budget small

lnk seed reads allowlisted project files such as README.md, AGENTS.md, CLAUDE.md, .cursorrules, and editor rule files, blocks secret-looking values, writes a source-backed project page, and rebuilds the graph. It does not create durable memories; agents should still use reviewed memory proposals for preferences and decisions.

The Homebrew formula is maintained in the public gowtham0992/homebrew-link tap.

Open:

http://127.0.0.1:3000
http://127.0.0.1:3000/onboard
http://127.0.0.1:3000/graph
http://127.0.0.1:3000/health

Use /onboard when you want the same first-run checklist in the local UI: readiness, project context seeding, first memory, agent wiring, and starter prompts. The web viewer is for local use only. It binds to 127.0.0.1, has no user accounts or authentication, and should not be exposed to the internet unless you add your own auth layer.

Try the value loop:

lnk start link-demo --task "working on agent memory"
lnk query "why does Link help agents?" link-demo --budget small
lnk brief "working on agent memory" link-demo
lnk benchmark "agent memory" link-demo
lnk health link-demo

lnk benchmark reports both performance and value evidence: cache/search/query timings, graph payload shape, and an estimate of how much broad wiki context the bounded Link packet avoided sending to an agent.

The /health page mirrors the readiness loop in the browser: validation state, interrupted writes, memory review status, and copyable repair commands. The viewer stays document-first — common paths in the top nav, deeper tools under more, and a contents outline plus graph-related links on structured pages.

The generated demo is the public proof wiki. Generated content inside wiki/, raw/, and link-demo/ is ignored by git so personal memory is not published by accident.

Killer Demo: One Memory, Two Agents

This is the moment Link is built for:

  1. In one agent, say:

    remember that I prefer local, source-backed memory for AI agents
    
  2. In another agent connected to the same ~/link workspace, say:

    start with Link before we continue
    what does Link remember about local agent memory?
    
  3. The second agent should recall the reviewed memory from local Markdown instead of asking you to repeat yourself.

For a clean automated version of the same idea, run:

lnk proof

Ways To Use Link

Pick the surface that matches how you work. They all read and write the same local Markdown wiki.

These surfaces are independent. lnk serve / serve.py is only the local web viewer. CLI commands, official skills, and MCP tools read the same wiki/ files directly, so Claude, Codex, Kiro, Cursor, or another agent can use Link even when the web viewer is not running.

Web UI
Read the local wiki, then review memory, ingest, graph, audits, captures, and explanations.
CLI
Script readiness, query packets, briefs, validation, backup, context-savings benchmark, and repair.
MCP
Let Codex, Claude, Cursor, Kiro, VS Code, Copilot, and other agents recall memory.

Link local console tour: home, memory dashboard, health, and graph

The local web viewer: browse source-backed memory and explore the knowledge graph — all on 127.0.0.1, no accounts, no backend.

Prefer skills instead of MCP? Link ships small, lazy-loadable CLI skills under skills/. They let an agent use lnk health, lnk query, lnk ingest-status, lnk session-end, and lnk remember directly, without MCP setup or a running web viewer.

skills/link-health/SKILL.md
skills/link-retrieve/SKILL.md
skills/link-ingest/SKILL.md
skills/link-memory/SKILL.md

Full guide: Link Skills.

Install For Your Agent

Run one installer from the cloned checkout:

bash integrations/codex/install.sh
bash integrations/kiro/install.sh
bash integrations/claude-code/install.sh
bash integrations/cursor/install.sh
bash integrations/copilot/install.sh
bash integrations/vscode/install.sh
bash integrations/antigravity/install.sh

Installers create or update ~/link, install or upgrade link-mcp, write lightweight agent instructions, and preserve existing wiki data on reinstall. Use --project when a repo needs separate project memory.

On Windows, use the matching PowerShell installer:

.\integrations\codex\install.ps1
.\integrations\kiro\install.ps1
.\integrations\claude-code\install.ps1
.\integrations\cursor\install.ps1
.\integrations\copilot\install.ps1
.\integrations\vscode\install.ps1
.\integrations\antigravity\install.ps1

Then ask your agent:

is Link ready?
start with Link before we continue
seed this project into Link
ingest raw/notes.md into Link
remember that I prefer short release notes
query Link for the release process
what does Link remember about local personal memory?
end this session with Link memory proposals

For CLI-first agents or Link skills, use the same startup loop directly:

lnk seed . ~/link
lnk start ~/link --task "working on Link release"
lnk session-end session-notes.md ~/link --limit 3

If you want one guided setup for a real workspace and an agent, use lnk onboard --agent AGENT. If your agent already has instructions and you only need MCP wiring, use the lower-level connection helper. Both preview the exact config first; add --write when you want Link to update the agent config file.

lnk onboard --agent codex
lnk onboard --agent codex --write
lnk connect codex ~/link
lnk connect codex ~/link --write
lnk connect kiro ~/link --write
lnk verify-mcp ~/link
MCP-only install
python3 -m pip install --upgrade link-mcp
python3 -m link_mcp --version
{
  "mcpServers": {
    "link": {
      "command": "python3",
      "args": ["-m", "link_mcp", "--wiki", "~/link/wiki", "--surface", "slim"]
    }
  }
}

--surface slim is the recommended MCP surface for agents: six obvious tools for recall, remember, ingest, review, status, and admin escape hatches. The full compatibility surface is still available with --surface full.

On macOS/Homebrew Python, if pip reports externally-managed-environment, use a dedicated venv:

python3 -m venv ~/.link-mcp-venv
~/.link-mcp-venv/bin/python -m pip install --upgrade pip link-mcp

Full setup: MCP guide.

Obsidian users can import an existing vault into raw/ for agent ingest, or open ~/link/wiki directly as a vault for editing Link pages:

lnk init ~/link
lnk import-obsidian ~/Documents/ObsidianVault ~/link

See the Obsidian guide for the import, edit, and validation loop.

Storage Model

Under the hood, Link separates source-backed knowledge from durable agent memory:

  1. Drop raw notes, transcripts, articles, and project context into raw/.
  2. Agents compile those sources into inspectable pages under wiki/.
  3. Explicit "remember" requests become reviewable memory pages.
  4. Queries retrieve compact agent context from both the wiki and memory layer.

Link architecture: raw sources become wiki knowledge, explicit remembers become reviewed memory, and agents retrieve compact context

The storage model is plain and inspectable:

LayerWhat lives there
raw/Original notes, transcripts, articles, PDFs, screenshots, and project files.
wiki/Source-backed pages, concepts, entities, explorations, comparisons, and memories.
Agent interfacesCLI, skills, MCP, and local viewer paths that avoid dumping the whole wiki into context.

If a raw file was already ingested and later edited, lnk ingest-status marks it as stale and tells your agent to refresh the existing source page instead of creating a duplicate.

What Agents Get

When an agent uses Link through the recommended MCP surface, it gets six model-facing tools. CLI and skill workflows call the same core behavior through lnk.

  • status: readiness, schema state, validation, interrupted writes, and safe next actions.
  • recall: the one read path for startup briefs, answer-ready query packets, wiki search, graph context, token budgets, and follow-up actions. Every recalled memory carries a confidence label (strong, moderate, weak), so agents verify weak lexical matches with the user instead of trusting them.
  • remember: durable local memory only after explicit user approval, with duplicate/conflict checks, provenance, review state, visibility, optional review_after, and optional expires_at.
  • ingest: exact next steps for raw files, source safety, stale ingest detection, validation, and rebuild checks.
  • review: memory inbox, profile, audit, log, explain, archive, restore, forget, and lifecycle review workflows.
  • admin: the escape hatch for backup, migrate, validate, graph export, pages, captures, rebuilds, compatibility actions, and advanced updates.

The stable agent-facing loop is documented at Link Memory Contract: readiness first, bounded recall, explicit memory writes, audit tools, and sharing semantics.

Use review_after for time-sensitive preferences or decisions. When that date arrives, the memory reappears in Link's review inbox so an agent can ask the user to confirm, update, archive, or forget it instead of trusting stale context. Use expires_at for temporary context that should automatically leave default recall after a date; Link keeps the Markdown page inspectable and asks the user to update, archive, or delete it. Use visibility to separate where a memory applies from who should see it: private stays personal, project is intended for a project workspace, and team means the user explicitly approved sharing it with a team.

For team handoff or security review, lnk compliance-export --output audit.json writes a redacted JSON packet with readiness, validation, memory review status, operation markers, and recent audit log entries. Raw source contents and memory bodies are not included.

For day-to-day auditability, lnk memory-log ~/link shows what Link recently remembered, updated, reviewed, archived, restored, forgot, or accepted from raw captures.

For recovery, lnk backup ~/link creates a local archive and lnk restore-backup <archive> ~/link previews what would be restored. Passing --confirm replaces local files after creating a safety backup when possible; raw/ is still excluded unless --include-raw is explicit. If a multi-file write is interrupted, lnk operations ~/link shows the marker and any rollback snapshot; lnk operations ~/link --recover <marker> --confirm restores the snapshot after you review it.

For local proof of value, lnk wins ~/link shows reusable memories, reviewed memory, provenance, project continuity, freshness guardrails, and copyable prompts without tracking user behavior.

For Git-backed team memory, lnk team-sync ~/link checks whether the workspace is ready to share reviewed wiki/ pages while keeping raw/, caches, backups, local MCP Python markers, and wiki/log.md private by default. The audit log is local because it has a single-machine hash chain; merging multiple users' logs would create false tamper alarms. Team sync also blocks "ready" status when the memory inbox is not clear or active visibility: private memories would be included by a broad git add wiki.

lnk team-sync ~/link --remote [email protected]:team/link-memory.git

For a teammate, reviewer, or another agent, lnk share resolves a page, memory, title, alias, or search phrase into a local viewer URL:

lnk share "Prefer local memory" ~/link

For a static, read-only review packet, lnk snapshot exports rendered wiki HTML without raw/, captures, operation markers, live MCP state, or memory pages by default. --include-memories exports only non-private memories; use --include-private-memories only for a personal archive or an explicitly approved review. It blocks export if wiki pages contain secret-looking values unless you explicitly override it.

lnk snapshot ~/link --output link-snapshot
lnk snapshot ~/link --output link-snapshot --include-memories --force
lnk snapshot ~/link --output personal-snapshot --include-memories --include-private-memories --force

Agent Contract

For MCP clients, agents should use Link in this order:

  1. status to check readiness and safe next actions.
  2. recall with an empty query once at the first substantive turn of a session.
  3. recall(query, budget="micro"|"small") before broad file reads or asking the user to repeat durable context.
  4. ingest before touching raw sources and after source edits for validation/rebuild checks.
  5. remember only when the user explicitly asks Link to remember something or approves a proposed memory.
  6. review for memory inbox, profile, audit, log, explain, archive, restore, and forget workflows.
  7. admin for backup, migration, graph export, captures, rebuilds, compatibility actions, and advanced maintenance.

Full MCP tool list: MCP setup.

Privacy And Safety

Link itself is local-first:

  • No telemetry in the installed CLI, MCP server, local web UI, or wiki runtime.
  • No hosted backend.
  • No external API calls from serve.py or link-mcp.
  • Raw sources and generated wiki pages are ignored by git by default.
  • lnk backup excludes raw/ unless you explicitly pass --include-raw.
  • Secret-looking API keys, provider tokens, JWTs, registry credentials, and private key blocks are detected in raw sources, captures, and release hygiene checks. lnk validate and lnk doctor also fail if secret-looking values are found inside wiki pages before they can be served through the local UI or returned through agent context.
  • The local web server binds to 127.0.0.1 and is not meant to be exposed to the internet without additional auth.

Before sharing a repo, demo, or wiki:

python3 link.py doctor
python3 link.py validate
python3 scripts/check_release_hygiene.py

More detail: Security guide.

Documentation

NeedGo here
Run Link for the first timeFirst 10 minutes
Decide whether Link fitsWhy Link?
Use the local viewerWeb UI
Understand raw/wiki/memoryConcepts
Configure MCPMCP setup
Find a commandCLI reference
Use Link without MCP setupOfficial skills
Use local HTTP endpointsHTTP API
Review security boundariesSecurity model
Check scale limits and measure your wikiLink Scale
Evaluate Link for a small teamTeam security review
Fix setup issuesTroubleshooting

Contributing

Contributions should come through pull requests targeting main. The develop branch is a maintainer integration branch for larger release work before it is proposed to main.

Before opening a PR:

python3 -m ruff check .
python3 -m pytest tests
python3 scripts/check_release_hygiene.py
python3 scripts/check_runtime_duplication.py
python3 scripts/check_tool_contract.py
git diff --check

Full contributor guide: Contributing.

Do not include personal wiki data, raw sources, registry tokens, .env files, or local MCP credentials in a PR.

If Link helps your agents remember better, star it on GitHub so more people can find it.