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Vlk MemAct

作者:aranajhonny版本 0.3.0i★ –i在你的电脑上运行
注册名称io.github.aranajhonny/vlk-core

安装

概览

作者提供的说明(英文原文)

Stateful memory for AI agents. Temporal awareness, error loop detection, and preventive constraints.

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这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

下载作者的 .mcpb 文件

链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。

在终端中运行这条命令

运行前请先填写空着的值。

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • DATABASE_URL env
    SQLite database path (default: sqlite:vlk.db?mode=rwc)

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 aranajhonny 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 5684 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5684 个服务器的 18% 更新
  • 基础检查结果等于或优于此分类中其他 5684 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Vlk MemAct 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.3.0)于5个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 MCPB。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

Up-to-date docs for AI agents

作者:upstash广泛使用↓ 97.3万/周★ 6.4万前天更新

电脑或云端

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

作者:DeusData广泛使用↓ 1.8万/周★ 4.8万22天前更新

在你的电脑上运行

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

作者:exa-labs正在增长★ 52132个月前更新

在云端运行✓ exa.ai

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Vlk² — Temporal State Machine for AI Agents

Vlk² gives AI agents a sense of time: what's happening now (PRESENT), what's already been tried (PAST), and what should guide future decisions (FUTURE). It runs as a single binary over MCP, backed by SQLite, and manages these temporal transitions autonomously.

The killer demo: when an agent repeats the same Rust/TS/Python/Go error 3 times, Vlk² auto-archives the loop and injects a preventive constraint so the agent stops retrying the same broken approach. But the architecture is general — the temporal state machine can track any kind of past→present→future transition across any agent framework.

What It Does

  • Temporal state machine — each memory has a state: PRESENT (active context), PAST (archived, hidden from context), FUTURE (preventive constraints), PURGED (forgotten). A background agent transitions entries between states without agent intervention.
  • Cross-language loop detection — fingerprints errors by language, not by string match. Recognizes Rust (error[E0277]), TypeScript/JS (TS2345, TypeError), Python (ValueError, KeyError), Go (panic: nil pointer), HTTP (503 Service Unavailable), test frameworks (expected: X, got: Y), with a timestamp-stripping fallback. When the same fingerprint appears ≥3 times, Vlk² auto-archives the loop to PAST and injects a FUTURE constraint.
  • Reconsolidation on retrieval — every recall checks current beliefs; if contradictory, the memory rewrites itself.
  • Token budget enforcement — every 30s, estimates total tokens in PRESENT + FUTURE. If over budget (8K default), archives lowest-importance entries until under budget.
  • Autonomous consolidation — background task (30s cycle) evaluates importance, archives stale entries, and forgets disconnected ones.

Why Not Just a Memory System?

General memory systems (agentmemory, Hindsight, Mem0, Supermemory) store facts, preferences, and context. Vlk² does one thing they don't: detect that the same Rust compile error repeated 3 times across different files and inject a constraint so the agent stops retrying the same broken approach. It's not a replacement — it's a specialized fault-detection layer that runs alongside them.

CapabilityVlk²agentmemoryHindsightSupermemory
Fact/persona memory—✅ 53 tools✅ hooks✅ keywords
Cross-language error fingerprinting✅ 7 strategies———
Autonomous loop breaking✅ ≥3 repeats auto-archive———
Reconsolidation on retrieval✅———
Token-bounded context✅ 8K default———

Quick Start

cd vlk-core

cargo build --release DATABASE_URL="sqlite:vlk.db?mode=rwc" ./target/release/vlk-core

Any MCP client connects via stdin/stdout — JSON-RPC 2.0, one line per message.

MCP Tools

ToolPurpose
vlk_record_statePush a log/error as a PRESENT slot for loop detection
vlk_fetch_contextClean context with reconsolidation + loop interception
vlk_time_travelArchive PRESENT → PAST and inject a FUTURE constraint
vlk_get_historyFull timeline audit
vlk_search_memoryKeyword search across logs and constraints
vlk_summarize_sessionState counts + token estimates
vlk_revoke_futureRemove incorrectly learned constraints
vlk_get_factsRetrieved distilled patterns
vlk_consolidation_statusShow consolidation agent state with token bar
vlk_pin_memoryProtect a pattern from forgetting
vlk_unpin_memoryRestore normal forgetting eligibility

How Loop Detection Works

  1. Each error is fingerprinted by type: Rust error[E...], TS TS..., Python TypeError:, Go panic:, HTTP 503, test assertion, or first-80-chars fallback
  2. Fingerprints group near-duplicates — same error code with different timestamps/line numbers count as one pattern
  3. At ≥3 repeats → auto-archives the loop + injects [SYSTEM ANCHOR] preventive constraint
  4. Future context fetches include the constraint, so the agent stops repeating

Architecture

memory_contents (immutable, team-agnostic)

└── FK ──► agent_timeline (PRESENT / PAST / FUTURE / PURGED) ├── memory_metadata (temporal vectors, importance, connectivity) └── semantic_facts (distilled patterns from errors) └── fact_contradictions (resolution tracking)

Consolidation Agent (background tokio, 30s cycle) SCAN → EVALUATE importance → BUDGET_CHECK → ARCHIVE low-value → FORGET stale

Verification

What's tested: the core loop detection path is verified: 3 identical Rust errors → auto-archive to PAST + FUTURE constraint injection. All 13 MCP tools respond correctly.

Not yet tested: pin/unpin with non-existent timeline_ids, token budget enforcement under load, conflict resolution.

Loop detection smoke test — sends the same Rust error[E0277] 3 times and verifies auto-archive + constraint injection:

import subprocess, json, tempfile, os, sys

db = tempfile.mktemp(suffix='.db') proc = subprocess.Popen(['./target/release/vlk-core'], stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.DEVNULL, env={'DATABASE_URL': f'sqlite:{db}?mode=rwc'})

def rpc(msg): proc.stdin.write((json.dumps(msg) + '\n').encode()) proc.stdin.flush() return json.loads(proc.stdout.readline())

Init

rpc({'jsonrpc':'2.0','id':1,'method':'initialize','params':{ 'protocolVersion':'2024-11-05','capabilities':{}, 'clientInfo':{'name':'test','version':'1.0'}}})

Send the same Rust error 3 times to trigger loop detection

error = 'error[E0277]: cannot add str to str' for i in range(3): r = rpc({'jsonrpc':'2.0','id':i+2,'method':'tools/call','params':{ 'name':'vlk_record_state', 'arguments':{'raw_log': error, 'file_context': f'lib.rs:{i*10}'}}}) assert 'PRESENT state recorded' in r'result'0 print(f' Record {i+1}: OK')

fetch_context triggers loop detection → auto-archive → constraint injection

r = rpc({'jsonrpc':'2.0','id':5,'method':'tools/call','params':{ 'name':'vlk_fetch_context','arguments':{}}}) txt = r'result'0 assert 'E0277' in txt, 'error missing after fetch' assert any(kw in txt for kw in ['SYSTEM ANCHOR', 'PREVENTIVE', 'CONSTRAINT']), \ 'no constraint injected' print(f' Fetch: loop archived + constraint injected')

proc.terminate(); proc.wait() for f in (db, db + '-wal', db + '-shm'): try: os.remove(f) except FileNotFoundError: pass print('PASS: loop detection works')

Integration

Add to Hermes, OpenCode, Claude Code, Codex, or any MCP host:

# ~/.hermes/config.yaml or equivalent

mcp_servers: vlk2: command: "vlk2" env: DATABASE_URL: "sqlite:~/.hermes/vlk/vlk.db?mode=rwc" timeout: 30

Compatible with any MCP client. Works alongside agentmemory, Hindsight, Supermemory, or Hermes built-in memory.

Requirements

  • Rust 2021 edition
  • SQLite (bundled via sqlx)
  • 6.4MB binary

Current Status

Actively developed. The core loop detection and corrective memory cycle is implemented and E2E-tested. Vlk² is a specialized complement to general memory systems — not a replacement.

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