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io.github.Mars-proj/verifiable-memory

PYPI · VERIFIABLE-MEMORY-MCP · SCANNED AUG 3

Memory for AI agents that can't hallucinate — cited or abstains, provable forget, deterministic.

−20 this week 13 Trust /100
Trust breakdown (6 categories)

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 →

Supply Chain Security38
  • Malware scan not yet available for this package.Unverified
  • No known CVEs affecting this package version or its production dependencies.Pass
  • Install-script risk not yet assessed.Unverified
  • No production dependencies, so there is no dependency health to assess. View diagnostics → Pass
Provenance & Transparency6
Schema Quality & AI Usability0
  • Schema quality not yet verified: our sandbox run of this package did not complete, so we have no schema to assess.Unverified
Stability & Change Management0
  • Stability not yet verified: our sandbox run of this package did not complete, so we have no schema to compare.Unverified
Tool Coverage0
  • Tool coverage not yet verified: our sandbox run of this package did not complete, so we have no tool definitions to assess.Unverified
Capabilities0
  • Protocol version not yet verified: our sandbox run of this package did not complete, so we never saw its MCP handshake.Unverified

Unverified: 4 categories

Categories scored 0 because our sandbox run of this package has not given us the schema these checks need to read. That is a gap on our side rather than a finding about the package, and we only credit what we can confirm, so the score stands at 0 until the capture succeeds. We are working through the fleet, so this normally clears without any action from you. How we score packages →

Install

Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.

pypi · verifiable-memory-mcp

# add to Claude Code
claude mcp add mars-proj-verifiable-memory -- uvx verifiable-memory-mcp
# add to Codex CLI
codex mcp add mars-proj-verifiable-memory -- uvx verifiable-memory-mcp
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "mars-proj-verifiable-memory": {
      "type": "local",
      "command": [
        "uvx",
        "verifiable-memory-mcp"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add mars-proj-verifiable-memory --command uvx --arg verifiable-memory-mcp
# ~/.hermes/config.yaml
mcp_servers:
  mars-proj-verifiable-memory:
    command: "uvx"
    args: ["verifiable-memory-mcp"]
// mcp.json
{
  "mcpServers": {
    "mars-proj-verifiable-memory": {
      "command": "uvx",
      "args": [
        "verifiable-memory-mcp"
      ]
    }
  }
}
Changelog

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.

  • 2 Aug 26 0
    • Malware scan: unverified → pass security
  • 1 Aug 26 −2
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 31 Jul 26 −18
    • Malware scan: pass → unverified security
  • 28 Jul 26 0
    • Tool coverage: Tool coverage not yet verified: our sandbox run of this package did not complete, so we have no tool definitions to assess. functional
    • Schema quality: Schema quality not yet verified: our sandbox run of this package did not complete, so we have no schema to assess. functional
  • 26 Jul 26 33

    First indexed and scored.

    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
Diagnostics

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 3 Aug 2026 · Analysed pypi/[email protected]

Provenance none

Ecosystem: pypi · Outcome: none

Dependencies 0 packages

0 packages in the resolved dependency tree.

MCP tools — 13 exposed · ~713 tokens

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.

Tool Tokens
all_paths ~46

All exact fact-paths between start and end entities (each path citable).

NameTypeReqDescription
endstringyes
max_depthnumber
startstringyes

No output schema declared.

No examples provided.

contradictions ~70

Audit knowledge for conflicts: for functional relations (one value expected, e.g. 'capital','birthdate') return any (subject,relation) holding >1 live value, showing BOTH sources — call before trusting facts that may have been updated or come from multiple sources.

NameTypeReqDescription
functional_relationsarrayyes

No output schema declared.

No examples provided.

forget ~84

Permanently and PROVABLY delete a stored fact (GDPR / right-to-be-forgotten). Use when the user asks to forget or remove information — the fact is fully erased and you get a signed proof of deletion. object optional (omit to delete all values).

NameTypeReqDescription
objectstring
relationstringyes
subjectstringyes

No output schema declared.

No examples provided.

history ~44

Full life-line of a fact (all versions live+closed, with sources and valid-time). Audit/compliance.

NameTypeReqDescription
relationstringyes
subjectstringyes

No output schema declared.

No examples provided.

knowledge_root ~21

Merkle root committing the entire current knowledge state (one hash).

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

learn_fact ~104

Store a fact (subject, relation, object) the agent must recall EXACTLY later, with its source. Call whenever the user states a fact, preference, decision, name, number, or rule worth remembering — it persists across sessions and is never silently distorted. Optional valid_from for valid-time.

NameTypeReqDescription
objectstringyes
relationstringyes
sourcestring
subjectstringyes
valid_fromnumber

No output schema declared.

No examples provided.

multihop ~58

Multi-hop chain: start entity + list of relations, follows subject->object each step (exact only, 0% hallucination).

NameTypeReqDescription
as_ofnumber
relationsarrayyes
startstringyes

No output schema declared.

No examples provided.

prove_fact ~40

Merkle inclusion proof that a fact is in the knowledge state (without revealing other facts).

NameTypeReqDescription
relationstringyes
subjectstringyes

No output schema declared.

No examples provided.

recall ~87

Look up a stored fact and return the answer WITH its cited source — or an honest 'unknown'. ALWAYS call this before answering a factual or memory question instead of guessing: it returns nothing rather than hallucinating, and includes a signed, verifiable receipt. Optional as_of for valid-time.

NameTypeReqDescription
as_ofnumber
relationstringyes
subjectstringyes

No output schema declared.

No examples provided.

stats ~13

Counts + current knowledge root.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

update_fact ~71

Update a fact's value without retraining: closes live versions (valid_to=t) and opens a new one. History is preserved.

NameTypeReqDescription
new_objectstringyes
relationstringyes
sourcestring
subjectstringyes
tnumber

No output schema declared.

No examples provided.

verify_proof ~43

Verify a Merkle inclusion proof (leaf, proof, root).

NameTypeReqDescription
leafstringyes
proofarrayyes
rootstringyes

No output schema declared.

No examples provided.

verify_receipt ~32

Verify a signed receipt returned by recall/forget (tamper-evident).

NameTypeReqDescription
receiptobjectyes

No output schema declared.

No examples provided.