Tibet Voice Cache Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Tibet Voice Cache Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
MCP server for persistent voice conversation memory. Plug into Claude Code, Cursor, Windsurf, or any MCP client.
pip install tibet-voice-cache-mcpGives any MCP-compatible AI client tools to store and recall voice conversation context. User and AI utterances are stored separately in RAM (or optionally on disk) and formatted as clean context summaries — no fake turns, no role confusion.
┌──────────────────────────────────────────────────────────────┐
│ MCP Client (Claude Code / Cursor / Windsurf / etc.) │
│ │
│ voice_cache_add(actor="user_1", text="...", role="user") │
│ voice_cache_add(actor="user_1", text="...", role="ai") │
│ voice_cache_turn(actor="user_1") │
│ │
│ voice_cache_inject(actor="user_1", │
│ base_instruction="You are a voice assistant.") │
│ → "You are a voice assistant. │
│ │
│ === PRIOR CONTEXT === │
│ The user previously said: │
│ - What's the weather? │
│ You previously responded: │
│ - Sunny and 22 degrees! │
│ === END CONTEXT ===" │
└──────────────────────────────────────────────────────────────┘// ~/.claude.json
{
"mcpServers": {
"voice-cache": {
"command": "tibet-voice-cache-mcp"
}
}
}{
"mcpServers": {
"voice-cache": {
"command": "tibet-voice-cache-mcp",
"env": {
"VOICE_CACHE_DIR": "/path/to/cache"
}
}
}
}Same pattern — add tibet-voice-cache-mcp as an MCP server command.
| Tool | Description |
|---|---|
voice_cache_status | List all active caches with stats |
voice_cache_open | Open/create cache for an actor |
voice_cache_add | Record user or AI utterance |
voice_cache_turn | Mark turn boundary |
voice_cache_context | Get formatted context summary |
voice_cache_inject | Inject context into system instruction |
voice_cache_session | Bulk import session transcripts |
voice_cache_history | View cached utterances |
voice_cache_clear | Clear cache for an actor |
voice_cache_configure | Change summary style / language |
# During voice session
voice_cache_open(actor="user_123")
voice_cache_add(actor="user_123", text="What's the weather?", role="user")
voice_cache_add(actor="user_123", text="Sunny and warm!", role="ai")
voice_cache_turn(actor="user_123")
# Next session — inject memory
voice_cache_inject(
actor="user_123",
base_instruction="You are a friendly weather assistant."
)Configure how context is formatted:
voice_cache_configure(actor="user_123", summary_style="compact")| Style | Format |
|---|---|
labeled | Sectioned with headers (default) |
compact | Minimal tokens, single-line |
narrative | Natural language, conversational |
chronological | Numbered turn pairs |
voice_cache_configure(actor="user_123", language="nl")Built-in: English (en), Dutch (nl).
| Variable | Default | Description |
|---|---|---|
VOICE_CACHE_DIR | _(none — RAM only)_ | Directory for JSON persistence |
VOICE_CACHE_MAX_TURNS | 50 | Max utterances per side before trimming |
VOICE_CACHE_STYLE | labeled | Default summary style |
The server also exposes MCP resources:
voice-cache://actors — List all actors with open cachesvoice-cache://actor/{name} — Full cache content for an actor| Package | Description |
|---|---|
tibet-voice-cache | Core library — voice conversation memory |
tibet-voice-cache-mcp | This package — MCP server wrapper |
MIT — plug it in, give your voice AI a memory.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.