
Vlk MemAct
io.github.aranajhonnyPublished by GitHub account aranajhonnyv0.3.0Updated Oct 28, 2026
Stateful memory for AI agents. Temporal awareness, error loop detection, and preventive constraints.
The publisher's own server: core.blue
Overview
A local SQLite-backed memory layer for AI agents that tracks past, present and future state and breaks repeated error loops.
- What you can do
- Record logs and errors as active memory slots, with automatic fingerprinting of repeated errors
- Fetch a clean context that rewrites contradictory memories and intercepts detected loops
- Archive current context and inject preventive constraints, then revoke constraints learned incorrectly
- Audit the full timeline, search logs and constraints by keyword, and list distilled patterns
- Summarize session state and token estimates, and check the background consolidation agent
- Pin or unpin patterns so they are protected from automatic forgetting
- When to use it
- Useful when an agent keeps retrying the same failing approach, such as the same compile error across files, and you want it to stop and remember the lesson. Also suits setups that need bounded context and automatic archiving of stale notes alongside another memory system.
- Requirements
- Runs as a local binary over stdio; the README describes building it with Rust and a bundled SQLite. The DATABASE_URL environment variable sets the SQLite database path (default sqlite:vlk.db?mode=rwc). No authentication is declared.
Installation
In SourceWeft
- Open Vlk MemAct in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
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.
Quick Start
Any MCP client connects via stdin/stdout — JSON-RPC 2.0, one line per message.
MCP Tools
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
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:
Integration
Add to Hermes, OpenCode, Claude Code, Codex, or any MCP host:
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.
Source: README.md at commit e14635c
Tools
0Version history
1- v0.3.0LatestSep 16, 2026
Score
40% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts
Declare a license in the repository or the registry entry.
Other Core integrations
core.blue
blue.coreOfficial publisher
Remote MCP endpoint for core.blue's private per-customer agent memory "houses": read its manual, try a sandbox, get pricing and recommendations, and request a…

Brevio Core
Published by GitHub account Brevio-Ventures
Local code-rule scanner for coding agents: scan diffs or files, explain rules, apply safe fixes, and turn a fix into a guard, with no model call.

brain-core
Published by GitHub account xy-claude
Local MCP server that gives a Claude Code agent persistent memory across sessions, stored as markdown files plus a SQLite and vector index on your disk.

Scovant Core
Published by GitHub account Scovant
Passive AI-agent readiness scan of a website: robots, llms.txt, JSON-LD, MCP discovery, security.

ProofCore
Published by GitHub account ProofCore-Protocol
Zero-Auth Cryptographic Notarization & Evidence Layer on TON Blockchain for AI Agents.