Turbo Quant Memory
PYPI · TURBO-QUANT-MEMORY · SCANNED SEP 20
Local-first memory and knowledge graph for coding agents. Compact retrieval, no network.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security82
- No malware found by supply-chain analysis.Pass
- CVE check failed: a known high-severity CVE affects cryptography 46.0.7, a direct dependency. A fixed version is available. View diagnostics → Fail
- Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- 16 of 92 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency32
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- License check failed: no license is declared. See how to fix → Fail
- Actively maintained (last published 0 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability59
- AI-judged instruction clarity (fair).Partial
- Tool/resource definitions use about 1653 tokens (~87/item across 19 items; 19 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management13
- Stability observed for 4 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage47
- 58% of tools have a non-trivial description (not blank, and not just the tool's name).Partial
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety75
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- 0 of 2 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "unlink_entities" implies "unlink" and declares no destructiveHint at all, which the MCP spec reads as destructive by default. See how to fix → Fail
- An AI judge read all 20 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the Turbo Quant Memory MCP server?
Turbo Quant Memory runs locally as a PyPI package, launched with uvx turbo-quant-memory. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · turbo-quant-memory
claude mcp add lexus2016-turbo-quant-memory -- uvx turbo-quant-memory
{
"mcpServers": {
"lexus2016-turbo-quant-memory": {
"command": "uvx",
"args": [
"turbo-quant-memory"
]
}
}
} {
"servers": {
"lexus2016-turbo-quant-memory": {
"command": "uvx",
"args": [
"turbo-quant-memory"
]
}
}
} codex mcp add lexus2016-turbo-quant-memory -- uvx turbo-quant-memory
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"lexus2016-turbo-quant-memory": {
"type": "local",
"command": [
"uvx",
"turbo-quant-memory"
],
"enabled": true
}
}
} openclaw mcp add lexus2016-turbo-quant-memory --command uvx --arg turbo-quant-memory
mcp_servers:
lexus2016-turbo-quant-memory:
command: "uvx"
args: ["turbo-quant-memory"] {
"McpServers": {
"lexus2016-turbo-quant-memory": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"turbo-quant-memory"
]
}
}
} assistant mcp add lexus2016-turbo-quant-memory -t stdio -c uvx -a turbo-quant-memory
{
"mcpServers": {
"lexus2016-turbo-quant-memory": {
"command": "uvx",
"args": [
"turbo-quant-memory"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 20 Sept 26 +2
- Stability: unverified → 0.13 ▲ functional
- Package version: 0.28.3 → 0.29.1 functional
- 18 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 17 Sept 26 −15
- Malware scan: pass → unverified ▼ security
- 16 Sept 26 54
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 20 Sept 2026 · Analysed pypi/turbo-quant-memory@0.29.1
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Vulnerabilities 7 findings
| ID | CVE | Severity | Vector | Fix available |
|---|---|---|---|---|
| GHSA-537c-gmf6-5ccf | high | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H | yes | |
| GHSA-g6cj-pr64-35w5 | CVE-2026-69247 | high | yes | |
| GHSA-jwv3-5hgf-82ww | CVE-2026-69249 | high | yes | |
| GHSA-m2h6-j472-rp4c | CVE-2026-69248 | medium | yes | |
| PYSEC-2026-3552 | CVE-2026-69247 | none | yes | |
| PYSEC-2026-3553 | CVE-2026-69249 | none | yes | |
| PYSEC-2026-3554 | CVE-2026-69248 | none | yes |
Background: What a vulnerability scan can and cannot prove →
Dependencies 92 packages
| Packages resolved | 92 |
|---|---|
| Stale | 15 |
| No linked repository | 1 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
delete_secret ~23
Delete a project secret by exact name.
| Name | Type | Req | Description |
|---|---|---|---|
| name | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
deprecate_note ~40
No description provided.
| Name | Type | Req | Description |
|---|---|---|---|
| note_id | string | yes | – |
| reason | – | – | – |
| replacement_note_id | – | – | – |
| replacement_scope | – | – | – |
| scope | string | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
get_related_entities ~92
Query relations involving a specific entity URI. uri: the entity to look up, as note://<note_id>, file://<relative/path>, issue://KEY, task://KEY, or https://... — the same URI forms link_entities accepts. Returns nothing for an entity that has no links yet.
| Name | Type | Req | Description |
|---|---|---|---|
| relation_type | – | – | – |
| scope | string | – | – |
| uri | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
get_secret ~84
Fetch a project secret by exact name. Returns the value in a dedicated ``secret_value`` field (never in descriptive text). Status is ``"ok"`` on hit, ``"missing"`` when no such name exists, or ``"error"`` with ``setup_hint`` when no master key is configured yet.
| Name | Type | Req | Description |
|---|---|---|---|
| name | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
health ~4
No description provided.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
hydrate ~26
No description provided.
| Name | Type | Req | Description |
|---|---|---|---|
| item_id | string | yes | – |
| mode | string | – | – |
| scope | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
index_paths ~94
Register and index Markdown directories into project memory. Supports .tqmemoryignore files (placed in project root or any indexed directory) with glob patterns to exclude paths from indexing. One pattern per line, # for comments. Example patterns: ``workspace-*`` skips any directory matching the glob; ``data/reports/*.md`` skips files matching a path pattern.
| Name | Type | Req | Description |
|---|---|---|---|
| mode | string | – | – |
| paths | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
link_entities ~100
Create a Knowledge Graph link between two entities. Entities are specified using URIs: - Note: note://<note_id> - File: file://<relative_path> (relative to project root) - External: e.g. issue://BUG-404, task://TASK-101
| Name | Type | Req | Description |
|---|---|---|---|
| relation_type | string | yes | – |
| scope | string | – | – |
| source_uri | string | yes | – |
| target_uri | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
lint_knowledge_base ~21
No description provided.
| Name | Type | Req | Description |
|---|---|---|---|
| max_issues | integer | – | – |
| paths | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
list_scopes ~6
No description provided.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
list_secrets ~21
List secret names in the active project. Never returns values.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
promote_note ~13
No description provided.
| Name | Type | Req | Description |
|---|---|---|---|
| note_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
recent_context ~180
Query-free session bootstrap: the most recently updated notes. Call this FIRST when starting a new session or resuming after a context compaction, when you do not yet know what to search for. Returns notes ordered by recency (newest first), NOT by relevance — including `handoff` notes (episodic tier), which a plain semantic_search hides by default. This is the reliable "where did I leave off" entry point. scope: 'project' (default), 'global', or 'hybrid'. Use 'hybrid' to also surface promoted cross-project knowledge. tier_filter: defaults to all tiers (so handoffs are included). Pass e.g. ["durable"] to exclude episodic session notes.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | – |
| scope | string | – | – |
| tier_filter | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
remember_note ~363
Store a typed project note. kind must be exactly one of: lesson, decision, pattern, handoff. tags: 2-3 lowercase tags are strongly recommended — tags are the only way to FILTER notes; an untagged note is reachable by semantic_search alone. source_refs: the files / notes / issues this note is about. Pass them as entity URIs (note://<id>, file://<relative/path>, issue://KEY, https://...) and they are auto-linked into the knowledge graph as `references` relations, so get_related_entities can later surface them. provenance: who originated the note. Use "human-explicit" when the USER asked to remember something ("remember this", "save that"); "agent" for your own observations (the default); "external-tool" for API/tool data; "system" for automatic processes. tier: normally derived from `kind` (handoff -> episodic, every other kind -> durable). Override e.g. tier="durable" to keep a `handoff` in the default-searchable set, or tier="episodic" to keep a noisy lesson out of regular search. After storing, connect the note with link_entities(source_uri="note://<id>", ...) when it relates to a file, issue, or prior note — the response echoes the note's uri and hints this when the note still has no relations.
| Name | Type | Req | Description |
|---|---|---|---|
| content | string | yes | – |
| kind | string | yes | – |
| provenance | string | – | – |
| scope | string | – | – |
| source_refs | – | – | – |
| tags | – | – | – |
| tier | – | – | – |
| title | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
self_test ~5
No description provided.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
semantic_search ~239
Compact memory retrieval (dense vector + BM25, fused via RRF). By default only the `durable` and `reference` tiers are searched, so session `handoff` notes (which live in the `episodic` tier) are NOT returned. To recover handoffs / session summaries pass ``tier_filter=["episodic"]`` (or list every tier to opt everything in). For a query-free "where did I leave off" bootstrap at session start, prefer the `recent_context` tool instead. source_filter narrows results by source type: ``"notes"`` returns only memory notes (decisions/lessons/patterns/handoffs), ``"markdown"`` only indexed doc blocks. In doc-heavy projects the reference blocks often crowd notes out of the top ranks on question-shaped queries — when you are asking "what did we decide/learn about X", pass ``source_filter="notes"``.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | – |
| query | string | yes | – |
| scope | string | – | – |
| source_filter | – | – | – |
| tier_filter | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
server_info ~5
No description provided.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
set_secret ~122
Store an encrypted secret in the active project's vault. The value is encrypted with AES-256-GCM under a per-project master key resolved from TQMEMORY_SECRETS_PASSPHRASE or the OS keyring. Secrets are NEVER indexed, embedded, or returned via ``semantic_search`` / ``hydrate``. They live in ``~/.turbo-quant-memory/projects/<project_id>/secrets/vault.tqv`` and stay on this machine.
| Name | Type | Req | Description |
|---|---|---|---|
| name | string | yes | – |
| value | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
unlink_entities ~79
Remove a Knowledge Graph link between two entities. source_uri / target_uri use the same URI forms as link_entities: note://<note_id>, file://<relative/path>, issue://KEY, https://...
| Name | Type | Req | Description |
|---|---|---|---|
| relation_type | – | – | – |
| scope | string | – | – |
| source_uri | string | yes | – |
| target_uri | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
What is the Turbo Quant Memory MCP server?
Turbo Quant Memory is an MCP server listed in the public MCP registry as io.github.Lexus2016/turbo-quant-memory. Local-first memory and knowledge graph for coding agents. Compact retrieval, no network. This page covers its PyPI package (turbo-quant-memory).
Is the Turbo Quant Memory MCP server safe to use?
Turbo Quant Memory scores 56 out of 100 on VerifyMCP. We recorded 7 known advisories against it as of 20 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Turbo Quant Memory MCP server expose?
Turbo Quant Memory exposes 19 tools: health, server_info, list_scopes, self_test, remember_note, and 14 more. Their descriptions and schemas cost roughly 1,517 tokens of context every time the server is loaded.
Is the Turbo Quant Memory MCP server still maintained?
Turbo Quant Memory is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.