Myelin MCP Server
myelin-mcp
PyPI
v0.3.0
Published by et-do — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
Neuromorphic long-term AI memory system — brain-inspired context for AI agents
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 7 = 93. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −6 | capability blast radius (high) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Findings 4
high Shell/command execution in server code (myelin/cli.py)MTC-SRC-002
In the server's implementation (`myelin/cli.py:1038`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: h) result = subprocess.run(sha_cmd, capture_output=True, text=True, check=True) all_shas = [ln.s
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server myelin/cli.py
high Shell/command execution in server code (myelin/integrations/github.py)MTC-SRC-002
In the server's implementation (`myelin/integrations/github.py:55`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: CompletedProcess[str] = subprocess.run( cmd, capture_output=True, text=True, **kwargs,
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server myelin/integrations/github.py
low Shell/command execution in packaging/dev tooling (tests/integrations/test_github.py)MTC-SRC-002
In a packaging/dev/install script (shipped, but not the server runtime) (`tests/integrations/test_github.py:25`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: rue, exist_ok=True) subprocess.run(["git", "init"], cwd=path, check=True, capture_output=True) subprocess.run(
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server tests/integrations/test_github.py
low Dynamic module load from a non-literal in packaging/dev tooling (tests/store/test_perirhinal.py)MTC-SRC-005
In a packaging/dev/install script (shipped, but not the server runtime) (`tests/store/test_perirhinal.py:85`): Loading a module chosen at runtime (from a variable) can pull in and run attacker-influenced code paths. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: embedder_for_query = __import__( "sentence_transformers", fromlist=["SentenceTransformer"] ).Sent
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server tests/store/test_perirhinal.py
Tools 11
Each tool and what it can reach — statically extracted from the published source.
consolidateno sensitive capabilitydecay_sweepno sensitive capabilityforgetno sensitive capabilityhealthno sensitive capabilityingestno sensitive capabilitypin_memoryno sensitive capabilityrecallno sensitive capabilitystatsno sensitive capabilitystatusno sensitive capabilitystoreno sensitive capability
Show 1 more tool ↓
unpin_memoryno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (11 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 1
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v0.3.0 latest |
A 93/100 | 4 | 1.13.0 | 2026-08-25 |
Embed this score
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
Verify this score yourself
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
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