github Python analyzed a117f92

jfr992/rekall-mcp

github

Persistent memory for AI assistants via MCP — semantic recall, knowledge graph, and a cockpit UI

maintainer
jfr992
license
Apache-2.0
first seen
2026-07-19
last seen
2026-07-19
releases · 30d
4
short id
risk 44/100 · heuristic grade
C elevated
  • capability exposure inferred + 35
  • recent drift inferred + 12
  • tool safety inferred + 5
  • trust mitigators mixed − 8

inferred mixed

The A–E grade is our heuristic synthesis — a "review this" prompt, not a verdict. Each factor is tagged by what backs it: attested (a verifiable record), reported (a third party's claim), or inferred (our own heuristic, e.g. permissions). See methodology.

graded 5m ago · see ecosystem CVEs →

risk trajectory 2 movements
  • C · 49 C · 44
  • B · 32 C · 49
capability exposure grade factor +35
Inferred surface — each links to servers holding it:
vulnerabilities 0 CVEs

No known CVEs for this server.

tool safety 2 findings · grade factor +5
  1. medium dangerous code

    dynamic exec: __import__()

  2. low dangerous code

    env-secret-flows-to-network-js: A process environment value (often a secret/token) flows into a network call — possible credential exfiltration. (jfr992-rekall-mcp-a117f92/ui/lib/a

skills & danger signals github-tarball
other grade factors evidence elsewhere
embed badge readme-ready
live risk-grade badge preview [![MCP Observatory risk grade](https://mcpobservatory.com/servers/github:jfr992/rekall-mcp/badge.svg)](https://mcpobservatory.com/servers/github:jfr992/rekall-mcp/security)

Heuristic, inferred signals — false positives (legitimately powerful tools, forks, language ports) are expected. Treat each as "review this", not a verdict. See the ecosystem-wide picture on the security hub, or the fleet security of jfr992.