Vlk MemAct
Stateful memory for AI agents. Temporal awareness, error loop detection, and preventive constraints.
What can you do with Vlk MemAct?
- 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)... - 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.
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
https://github.com/aranajhonny/vlk/releases/download/v0.3.0/vlk-core-x86_64-unknown-linux-gnu.mcpbEnvironment variables
DATABASE_URLSQLite database path (default: sqlite:vlk.db?mode=rwc)
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Contents
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.
| Capability | Vlk² | agentmemory | Hindsight | Supermemory |
|---|---|---|---|---|
| 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
| Tool | Purpose |
|---|---|
vlk_record_state | Push a log/error as a PRESENT slot for loop detection |
vlk_fetch_context | Clean context with reconsolidation + loop interception |
vlk_time_travel | Archive PRESENT → PAST and inject a FUTURE constraint |
vlk_get_history | Full timeline audit |
vlk_search_memory | Keyword search across logs and constraints |
vlk_summarize_session | State counts + token estimates |
vlk_revoke_future | Remove incorrectly learned constraints |
vlk_get_facts | Retrieved distilled patterns |
vlk_consolidation_status | Show consolidation agent state with token bar |
vlk_pin_memory | Protect a pattern from forgetting |
vlk_unpin_memory | Restore normal forgetting eligibility |
How Loop Detection Works
- Each error is fingerprinted by type: Rust
error[E...], TSTS..., PythonTypeError:, Gopanic:, HTTP503, test assertion, or first-80-chars fallback - Fingerprints group near-duplicates — same error code with different timestamps/line numbers count as one pattern
- At ≥3 repeats → auto-archives the loop + injects
[SYSTEM ANCHOR]preventive constraint - 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']['content'][0]['text']
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']['content'][0]['text']
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.
Frequently asked questions
What is Vlk MemAct?
Stateful memory for AI agents. Temporal awareness, error loop detection, and preventive constraints.
How do I install Vlk MemAct?
Follow the installation steps in its documentation, shown on this page and in its repository.
Does Vlk MemAct need an API key?
Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.
Is Vlk MemAct open source?
Its code is public on GitHub, but the repository does not declare a standard license.
Who maintains Vlk MemAct?
It is published by aranajhonny. AI.tn lists it but does not maintain or endorse it.
From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.