에이전트 강화
게시자의 자체 명령입니다. PlugMCP 엔드포인트가 아닙니다.
Host a copy with our keys and logs.
npx -y @putervision/[email protected]Claude Code에는 로컬 명령용 설치 링크가 없습니다. 아래 명령을 복사해 터미널에서 실행합니다.
claude mcp add putervision-state-memory-mcp -- npx -y @putervision/state-memory-mcp@1.4.1터미널에서 실행합니다.
{ "mcpServers": { "putervision-state-memory-mcp": { "command": "npx", "args": [ "-y", "@putervision/[email protected]" ] } }}claude_desktop_config.json
원격 URL인가요, 내 컴퓨터에서 실행하는 명령인가요? 두 설치 방식의 차이
PlugMCP에서 실행
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
실행@putervision/state-memory-mcp is a zero-infrastructure, deterministic Model Context Protocol (MCP) server that provides AI coding assistants (such as Cursor, Claude Code, Gemini, or Copilot) with a structured, persistent SQLite graph for tracking workflow state—tasks, decisions, artifacts, plans, blockers, and their semantic relationships.
🌐 Official Documentation & Website: statememorymcp.com
Prerequisites: Node.js >= 18.18.0
# 1. Install globally
npm install -g @putervision/state-memory-mcp
# 2. Navigate to your project directory
cd your-project
# 3. Initialize state-memory-mcp
# Creates .state-memory-mcp/, updates .gitignore, registers project,
# and scaffolds IDE instructions and MCP configs for Cursor, Claude, VS Code, Windsurf, etc.
state-memory-mcp init
# Done! Restart your IDE or Agent Manager to activate.
# Run directly via binary (after global install)
state-memory-mcp run
# Re-initialize across all registered workspace projects
state-memory-mcp init-global
TaskSlice extraction for System 1 fast path evaluation.state-memory-mcp view).@putervision/vision-memory-mcp for visual state caching, perceptual hashing, and cryptographic multimodal evidence packs..state-memory-mcp/ in your workspace.@putervision/state-memory-mcp provides 13 production-grade consolidated MCP tools organized across 5 core workflow domains:
manage_nodes (node CRUD, FTS5/TF-IDF vector search, atomic batch mutations, observation notes, thresholded fast decision logging), manage_edges (typed DAG links, multimodal visual state linking).manage_tasks (topological dependency queue, blocker detection, task completion with artifacts, auto-prune), manage_sessions (agent attribution, turn tracking, context bootstrap).manage_specs (PRD/RFC parsing, requirement-to-task decomposition, live acceptance criteria verification, compliance scoring).get_analytics (velocity, burndown, token ROI, cognitive load, critical path), get_events (SHA-256 tamper-evident event ledger), run_diagnostics (DAG validation, health checks, AST reference integrity).manage_snapshots (checkpoints, time-travel undo), manage_database (backups, checksum audits, VCS branch merge), manage_data (bulk import/export, ML trajectories with interleaved fast decision events), query_graph (subgraphs, dependency tracing, raw SQL, sub-1KB compact_slice), use_blackboard (multi-agent asynchronous topic board).👉 For complete parameter specifications, return schemas, and example payloads, see the Tools Reference Guide and Formal API Reference.
AI Agent Prompt / Task
│
▼
┌─────────────────────────────────┐
│ Agent Session Attribution │ ──▶ manage_sessions(action: "start")
└────────────────┬────────────────┘
│
▼
┌─────────────────────────────────┐
│ Context & Task Prioritization │ ──▶ get_analytics(action: "summary")
│ │ ──▶ manage_tasks(action: "next")
└────────────────┬────────────────┘
│
▼
┌─────────────────────────────────┐
│ Deterministic Graph Mutation │ ──▶ manage_nodes(action: "create"|"update")
│ (Tasks, Decisions, Blockers) │ ──▶ manage_edges(action: "add"|"link_visual")
└────────────────┬────────────────┘
│
▼
┌─────────────────────────────────┐
│ Spec & Integrity Verification │ ──▶ manage_specs(action: "compliance"|"verify")
│ │ ──▶ run_diagnostics(action: "validate")
└────────────────┬────────────────┘
│
▼
┌─────────────────────────────────┐
│ Persistent SQLite Storage │ ──▶ .state-memory-mcp/graph.db (WAL mode)
│ Append-Only Event Ledger │ ──▶ SHA-256 Cryptographic Audit Chain
└─────────────────────────────────┘
Explore dedicated guides and deep dives in the docs/ directory:
When an autonomous AI agent enters a repository with state-memory-mcp:
1. Orient & Bootstrap ──▶ manage_sessions(action: "start") + get_analytics(action: "summary")
2. Task Selection ──▶ manage_tasks(action: "next") + manage_tasks(action: "find_blockers")
3. Trace Context ──▶ query_graph(action: "trace") + manage_specs(action: "compliance")
4. Execute & Record ──▶ manage_nodes(action: "create", type: "decision") + manage_edges(action: "link_visual")
5. Validate & Close ──▶ run_diagnostics(action: "validate") + manage_tasks(action: "complete") + manage_sessions(action: "end")
# Run full unit, integration, and performance benchmark test suite across all 113 test files (418 tests)
npm run test
Developed and maintained by PuterVision. Released under the MIT License.
Deterministic, persistent graph server for tracking workflow state, decisions, and blockers.
{ "mcpServers": { "putervision-state-memory-mcp": { "command": "npx", "args": [ "-y", "@putervision/[email protected]" ] } }}도구
아직 도구 목록이 없습니다. 원격 서버는 첫 상태 확인 후에 도구 목록이 생깁니다.
FAQ
이 페이지에서 Cursor, Claude Desktop, Claude Code 또는 VS Code용 stdio 설정을 복사합니다. PlugMCP 프록시가 아니라 게시자의 설치 방식을 사용합니다.
이 레코드에는 필수 환경 변수가 등록되어 있지 않습니다.
@putervision/state Memory은(는) stdio를 통해 로컬에서 실행됩니다.
마지막 확인: 2026-11-09. Deterministic, persistent graph server for tracking workflow state, decisions, and blockers.