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NeuroDock Task Fractionator

PYPI · NEURODOCK-MCP-TASK-FRACTIONATOR · SCANNED SEP 20

Decompose a vague goal into atomic 5-90 minute tasks and surface the next safe action.

−15 this week 66 Trust /100
Trust breakdown (7 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 → 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 93 days ago).Pass
  • Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability72
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 368 tokens (~184/item across 2 items; 2 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management83
  • Stability observed for 25 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage90
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 67% 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 2 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 2 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
Install

How do I install the NeuroDock Task Fractionator MCP server?

NeuroDock Task Fractionator runs locally as a PyPI package, launched with uvx neurodock-mcp-task-fractionator. 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-task-fractionator

# add to Claude Code
claude mcp add tlennon-ie-neurodock-mcp-task-fractionator -- uvx neurodock-mcp-task-fractionator
// .cursor/mcp.json
{
  "mcpServers": {
    "tlennon-ie-neurodock-mcp-task-fractionator": {
      "command": "uvx",
      "args": [
        "neurodock-mcp-task-fractionator"
      ]
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "tlennon-ie-neurodock-mcp-task-fractionator": {
      "command": "uvx",
      "args": [
        "neurodock-mcp-task-fractionator"
      ]
    }
  }
}
# add to Codex CLI
codex mcp add tlennon-ie-neurodock-mcp-task-fractionator -- uvx neurodock-mcp-task-fractionator
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "tlennon-ie-neurodock-mcp-task-fractionator": {
      "type": "local",
      "command": [
        "uvx",
        "neurodock-mcp-task-fractionator"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add tlennon-ie-neurodock-mcp-task-fractionator --command uvx --arg neurodock-mcp-task-fractionator
# ~/.hermes/config.yaml
mcp_servers:
  tlennon-ie-neurodock-mcp-task-fractionator:
    command: "uvx"
    args: ["neurodock-mcp-task-fractionator"]
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "tlennon-ie-neurodock-mcp-task-fractionator": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "neurodock-mcp-task-fractionator"
      ]
    }
  }
}
# add to Vellum
assistant mcp add tlennon-ie-neurodock-mcp-task-fractionator -t stdio -c uvx -a neurodock-mcp-task-fractionator
// mcp.json
{
  "mcpServers": {
    "tlennon-ie-neurodock-mcp-task-fractionator": {
      "command": "uvx",
      "args": [
        "neurodock-mcp-task-fractionator"
      ]
    }
  }
}
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.

  • 19 Sept 26 −3
    • Stability: pass → 0.80 functional
  • 18 Sept 26 +1
    • Stability: 0.97 → pass security
  • 17 Sept 26 −15
    • Malware scan: pass → unverified security
  • 16 Sept 26 +16
    • Malware scan: unverified → pass security
  • 14 Sept 26 −14
    • Malware scan: pass → unverified security
  • 12 Sept 26 +12
    • Malware scan: unverified → pass security
    • Stability: pass → 0.80 functional
  • 11 Sept 26 +1
    • Stability: 0.97 → pass security
  • 10 Sept 26 −15
    • Malware scan: pass → unverified security
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 20 Sept 2026 · Analysed pypi/neurodock-mcp-task-fractionator@0.1.0

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 →

MCP tools · 2 exposed · ~368 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. 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 →

Tool Tokens
decompose ~317

Break a vague goal into a small ordered list of atomic 5-90 minute tasks with explicit acceptance criteria and dependency edges. Stateless: returns tasks but does NOT persist them.

NameTypeReqDescription
goalstringyes
max_chunk_sizeOptional neurotype knob (ADR 0011). Caps the NUMBER of tasks returned, below the normal 3-12 target / hard cap of 20. When the goal naturally needs more steps, the server keeps the lowest-sequence pr…
motor_fatigue_awareOptional neurotype knob (ADR 0011). When true, the server echoes the preference and names it in the rationale so the client can act on it. The server has no view of actual motor activity and does NOT…
time_budgetOptional total time budget as an ISO-8601 duration, e.g. 'PT2H' (2 hours) or 'PT90M' (90 minutes) — not prose like 'a couple of hours'.
time_buffer_multiplierOptional neurotype knob (ADR 0011). When greater than 1.0, the server attaches an additive 'padded_minutes' to each task equal to round(estimated_minutes * multiplier). 'estimated_minutes' stays RAW…

Structured output declared, but exposes no named fields.

No examples provided.

next_one ~51

Return exactly one task for the given project — the single thing the user should do next — with reasoning and a confidence number. Errors with NO_TASKS_AVAILABLE when nothing is pending.

NameTypeReqDescription
projectstringyes

Structured output declared, but exposes no named fields.

No examples provided.

Common questions

What is the NeuroDock Task Fractionator MCP server?

NeuroDock Task Fractionator is an MCP server listed in the public MCP registry as io.github.tlennon-ie/neurodock-mcp-task-fractionator. Decompose a vague goal into atomic 5-90 minute tasks and surface the next safe action. This page covers its PyPI package (neurodock-mcp-task-fractionator).

Is the NeuroDock Task Fractionator MCP server safe to use?

NeuroDock Task Fractionator scores 66 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 Task Fractionator MCP server expose?

NeuroDock Task Fractionator exposes 2 tools: decompose, next_one. Their descriptions and schemas cost roughly 368 tokens of context every time the server is loaded.

Is the NeuroDock Task Fractionator MCP server still maintained?

NeuroDock Task Fractionator 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 Task Fractionator MCP server under?

NeuroDock Task Fractionator 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.