NeuroDock Guardrail
PYPI · NEURODOCK-MCP-GUARDRAIL · SCANNED SEP 20
Advisory detectors for rumination, hyperfocus, and sycophancy. Never silently blocks.
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 Security50
- Malware scan not yet available for this package.Unverified
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- 1 of 15 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency48
- 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
- Clear OSI-approved license (AGPL-3.0-or-later).Pass
- Actively maintained (last published 100 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability57
- AI-judged instruction clarity (fair).Partial
- Tool/resource definitions use about 304 tokens (~101/item across 3 items; 3 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management80
- Stability observed for 24 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage76
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 15% of tool parameters carry a description.Partial
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 3 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 3 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
How do I install the NeuroDock Guardrail MCP server?
NeuroDock Guardrail runs locally as a PyPI package, launched with uvx neurodock-mcp-guardrail. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · neurodock-mcp-guardrail
claude mcp add tlennon-ie-neurodock-mcp-guardrail -- uvx neurodock-mcp-guardrail
{
"mcpServers": {
"tlennon-ie-neurodock-mcp-guardrail": {
"command": "uvx",
"args": [
"neurodock-mcp-guardrail"
]
}
}
} {
"servers": {
"tlennon-ie-neurodock-mcp-guardrail": {
"command": "uvx",
"args": [
"neurodock-mcp-guardrail"
]
}
}
} codex mcp add tlennon-ie-neurodock-mcp-guardrail -- uvx neurodock-mcp-guardrail
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"tlennon-ie-neurodock-mcp-guardrail": {
"type": "local",
"command": [
"uvx",
"neurodock-mcp-guardrail"
],
"enabled": true
}
}
} openclaw mcp add tlennon-ie-neurodock-mcp-guardrail --command uvx --arg neurodock-mcp-guardrail
mcp_servers:
tlennon-ie-neurodock-mcp-guardrail:
command: "uvx"
args: ["neurodock-mcp-guardrail"] {
"McpServers": {
"tlennon-ie-neurodock-mcp-guardrail": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"neurodock-mcp-guardrail"
]
}
}
} assistant mcp add tlennon-ie-neurodock-mcp-guardrail -t stdio -c uvx -a neurodock-mcp-guardrail
{
"mcpServers": {
"tlennon-ie-neurodock-mcp-guardrail": {
"command": "uvx",
"args": [
"neurodock-mcp-guardrail"
]
}
}
} 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 −18
- Malware scan: pass → unverified ▼ security
- Stability: pass → 0.80 functional
- 19 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- Stability: 0.97 → pass security
- 18 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 17 Sept 26 −15
- Malware scan: pass → unverified ▼ security
- 16 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
- 15 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 14 Sept 26 −14
- Malware scan: pass → unverified ▼ security
- 13 Sept 26 −3
- Stability: pass → 0.80 functional
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/neurodock-mcp-guardrail@0.0.5
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 →
Dependencies 15 packages
| Packages resolved | 15 |
|---|---|
| Stale | 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 →
check_hyperfocus Check hyperfocus ~173
Classify hyperfocus escalation from a caller-supplied chronometric snapshot into one of (none, gentle, nudge, hard). Stateless; quotes prior_intent verbatim.
| Name | Type | Req | Description |
|---|---|---|---|
| chronometric_snapshot | object | yes | Current timing snapshot. Required: 'now' (ISO-8601 timestamp). Optional: 'open_session' as {'session_id', 'started_at' (ISO-8601), 'intent', 'elapsed_seconds'} or null when no session is open, and 'i… |
| end_of_day_local | – | – | Local end-of-day time as HH:MM, 24-hour, e.g. '18:00'. |
| escalation_thresholds | – | – | – |
| hyperfocus_break_minutes | integer | – | – |
| session_id | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
check_rumination Check rumination ~75
Detect whether the user's current prompt is a semantic repeat of recent prompts within a rolling window. Stateless; returns a structured advisory signal.
| Name | Type | Req | Description |
|---|---|---|---|
| current_prompt | string | yes | – |
| history | array | yes | – |
| similarity_threshold | number | – | – |
| threshold_count | integer | – | – |
| window_minutes | integer | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
check_sycophancy Check sycophancy ~56
Detect over-validation in a candidate response or repeated reassurance-seeking in recent user messages. Returns a counter_prompt the caller MAY surface.
| Name | Type | Req | Description |
|---|---|---|---|
| candidate_response | – | – | – |
| decision_context | – | – | – |
| recent_user_messages | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
What is the NeuroDock Guardrail MCP server?
NeuroDock Guardrail is an MCP server listed in the public MCP registry as io.github.tlennon-ie/neurodock-mcp-guardrail. Advisory detectors for rumination, hyperfocus, and sycophancy. Never silently blocks. This page covers its PyPI package (neurodock-mcp-guardrail).
Is the NeuroDock Guardrail MCP server safe to use?
NeuroDock Guardrail scores 62 out of 100 on VerifyMCP. We found no known CVEs affecting 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 NeuroDock Guardrail MCP server expose?
NeuroDock Guardrail exposes 3 tools: check_rumination, check_hyperfocus, check_sycophancy. Their descriptions and schemas cost roughly 304 tokens of context every time the server is loaded.
Is the NeuroDock Guardrail MCP server still maintained?
NeuroDock Guardrail 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.
What licence is the NeuroDock Guardrail MCP server under?
NeuroDock Guardrail declares the AGPL-3.0-or-later licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.