Shared Workspace
БесплатноНе проверенLocal-first memory, pipelines, learning, feedback, and safe code tools for AI coding agents.
Описание
Local-first memory, pipelines, learning, feedback, and safe code tools for AI coding agents.
README
Shared memory & verified handover for AI agents.
Codex and Cowork pass work back and forth without losing the thread — and can't fake "done".
“Cairn” is the unofficial name for the Shared Workspace MCP (shared-workspace-mcp).
🔄 The gated pipeline
🏆 Earn the level
✨ What it does
| 🧠 Memory | shared KV · activity · file events | survives restarts & handovers |
| 🤝 Handover | one-call prepare / takeover | Codex ⇄ Cowork, nothing dropped |
| 🚦 Gates | hard vs advisory, evidence-graded | blocks self-declared "done" |
| 🕵️ Freshness | chain-of-custody on evidence | a stale check is not proof |
| 👀 Four-eyes | source-tracked checks | warns on self-certification |
| 🛎️ Andon | blocked gate → logged lesson | failures compound into learning |
| 🏅 Self-score | 0–10, evidence-based | quality trend, not vanity |
| 🔒 Safe | localhost · home-scoped · preset checks | no arbitrary shell |
⚡ Setup — one command
Windows (PowerShell)
powershell -NoProfile -ExecutionPolicy Bypass -Command "irm https://raw.githubusercontent.com/WhileTrueBlackObelizk/shared-workspace-mcp/main/install.ps1 | iex"
Linux (systemd user service)
curl -fsSL https://raw.githubusercontent.com/WhileTrueBlackObelizk/shared-workspace-mcp/main/install.sh | bash
Then point your MCP client at:
http://localhost:8765/sse
Claude Code can also spawn it over stdio:
claude mcp add --scope user shared-workspace -- python /path/to/shared-mcp/server.py --stdio
On Windows the installer wires up the Claude Desktop / Cowork config and removes the older duplicate local extension if present. Restart Claude, then ask Cowork for workspace_dump or gate_check. Liveness: GET http://localhost:8765/health.
Data hygiene - local memory, public code
The repository contains the MCP server and installer only. Your actual agent memory is local runtime data under:
~/.claude/shared-workspace/
That directory is not part of this repo and should not be committed. It may contain project names, handovers, file paths, decisions, and logs from your machine.
The hot workspace should stay small:
active_task
session_owner
context
current_plan
acceptance_criteria
last_output
next_steps
blockers
handover_notes
workspace_health
Long project notes belong in project files, docs, or namespaced project keys.
workspace_dump prints hot keys in full, previews long cold keys, and points to
workspace_read for the full value.
🚀 Usage — the whole trick
Compact state outside the prompt, pulled only when it matters:
workspace_dump
workspace_audit
workspace_maintain
mcp_doctor
get_recent_activity n=10
learning_search query="similar failure"
learning_context query="current task"
gate_check step=test root="C:\path\to\repo" source=cowork
gate_advance pipeline_id=my-task root="C:\path\to\repo" source=cowork
drift_report pipeline_id=my-task
goal_complete goal_id=my-task # self-scores + levels up
Default pipeline: intake → plan → implement → test → review → handover.
Advance with gate_advance (not manual edits); a blocked gate writes a lesson.
Maintenance guards
handover_takeover runs safe maintenance and a lightweight doctor summary
before it returns context. It does not delete project knowledge. It only removes
stale temporary JSON files and writes a small workspace_health key.
It reports attention when:
workspace_dump is too large
one hot key is too long
active context and current_plan mention different projects
current_plan is stale
old temporary files exist
many completed pipelines remain in the live store
more than one goal is active
Use workspace_audit to inspect the full report and workspace_maintain to run
the same safe cleanup manually.
Use mcp_doctor when investigating runtime or process issues. It checks
runtime/file drift, workspace hygiene, and duplicate server.py registrations,
then returns recommended next actions.
Many observed server processes are reported as an informational hint when they
map to distinct clients; duplicate registrations remain the warning condition.
Takeovers include the lightweight doctor summary automatically. Call mcp_doctor
directly when you also need the process probe.
Takeovers also include learning_context, an automatic relevance pass over
stored lessons using the active task and current plan. Agents still can call
learning_search, but routine starts do not depend on remembering to ask.
Writing active_task also records a task_start activity automatically, so the
intake gate does not depend on a second manual log call.
🧰 Tools
| Area | Tools |
|---|---|
| Memory | workspace_write · workspace_read · workspace_dump · workspace_list · workspace_delete |
| Maintenance | workspace_audit · workspace_maintain · mcp_doctor |
| Activity / files | log_activity · get_recent_activity · get_file_events |
| Handover | handover_prepare · handover_takeover |
| Code workspace | repo_status · git_diff · search_code · read_file · run_check (ruff/mypy too) |
| Gates | gate_policy · gate_check · gate_status · gate_advance · verify_file_refs · drift_report |
| Goals / pipelines | goal_start · goal_update · goal_status · goal_complete · pipeline_create · pipeline_next · pipeline_status · pipeline_update_step · pipeline_finish |
| Learning | learning_log_error · learning_log_lesson · learning_search · learning_context · learning_recent |
| Tokens / feedback | token_log · token_summary · estimate_tokens · context_snapshot · feedback_maybe · feedback_log · feedback_summary |
🔒 Security & 🏗️ Architecture
- Binds
127.0.0.1only · file paths must stay under your home ·run_checkruns fixed presets, never arbitrary shell. - Storage: UTF-8 JSON under
~/.claude/shared-workspace/. No hosted DB, no paid service. - Deep dives: ARCHITECTURE.md · handover-protocol.md · SECURITY.md · agent rules in AGENTS.md.
Установка Shared Workspace
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/WhileTrueBlackObelizk/shared-workspace-mcpFAQ
Shared Workspace MCP бесплатный?
Да, Shared Workspace MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Shared Workspace?
Нет, Shared Workspace работает без API-ключей и переменных окружения.
Shared Workspace — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Shared Workspace в Claude Desktop, Claude Code или Cursor?
Открой Shared Workspace на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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