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io.github.degibug-del/laserbrain

PYPI · LASERBRAIN

The drift harness as an MCP server. Offline, no key — a fixed reference an agent checks against.

Available components

+1 this week 59 Trust /100

Last scanned (11 hours ago)

Scores higher than 57% of PyPI servers

Category AI and Machine Learning

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 setuptools.build_meta at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
  • No production dependencies, so there is no dependency health to assess. View diagnostics → Pass
Provenance & Transparency19
Schema Quality & AI Usability69
  • AI-judged instruction clarity (good).Pass
  • Tool/resource definitions use about 427 tokens (~61/item across 7 items; 7 tools + 0 resources), lean.Pass
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
  • No destabilizing schema changes in the last 30 days.Pass
Tool Coverage81
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 43% of tool parameters carry a description.Partial
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 7 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 7 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities20
  • Spec-recency check failed: implements MCP spec 2024-11-05; the latest is 2026-07-28. See how to fix → Fail
What we tested

Checks we ran (14)

  • Known CVEs
  • Install scripts
  • Dependency health
  • Source repository
  • Provenance
  • License
  • Maintenance
  • Schema quality
  • Stability
  • Tool coverage
  • Injection markers
  • Destructive annotations
  • Judged manipulation
  • MCP protocol

Checks we could not complete (2)

These are gaps on our side, not findings about this package. We only credit what we can confirm, so a category made up entirely of them scores 0.

  • Malware scan in Supply Chain SecurityMalware scan not yet available for this package.
  • Security disclosure in Provenance & TransparencySecurity-disclosure policy not yet verified: we couldn't inspect the source repository.

Does not apply to this package (2)

  • Endpoint SecurityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.
  • Transport & ReachabilityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.

The score does not measure everything. What the score does not measure →

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.

  • 5 Nov 26 −15
    • Malware scan: pass → unverified ▼ security
  • 4 Nov 26 +15
    • Malware scan: unverified → pass ▲ security
  • 3 Nov 26 −15
    • Malware scan: pass → unverified ▼ security
  • 31 Oct 26 +16
    • Malware scan: unverified → pass ▲ security
    • Stability: 0.97 → pass security
  • 29 Oct 26 −16
    • Malware scan: pass → unverified ▼ security
    • Stability: pass → 0.93 functional
  • 25 Oct 26 +15
    • Malware scan: unverified → pass ▲ security
  • 24 Oct 26 −15
    • Malware scan: pass → unverified ▼ security
  • 23 Oct 26 +15
    • Malware scan: unverified → pass ▲ 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 5 Nov 2026 · Analysed pypi/laserbrain@0.29.0

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result No attestation
Ecosystem pypi
Reason No attestation published

Background: How many MCP packages publish verified provenance →

Install scripts 1 script
Hook Tier Command
build_backend Known build tool setuptools.build_meta

Background: Why install scripts are a supply-chain risk →

Dependencies 0 packages
Packages resolved 0
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 7 exposed · ~427 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
capabilities ~21

What this server can do offline, and what needs the hosted one.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

check_state ~113

Spell where you are. The FIRST call freezes the ground — every later reading is measured against it, which is what makes this different from asking yourself. Call it each step. Returns one of nine verdicts, Φ, and what to do.

NameTypeReqDescription
distancenumber–How far from done, 0-10. 0 means finished.
goalstringyesWhat you are working on, in your own words.
progressstring–Honestly. A false "advancing" wastes the reading.

No output schema declared.

No examples provided.

get_history ~32

The checks spelled so far this session, and how many were drifting.

NameTypeReqDescription
limitnumber–Default 20.

No output schema declared.

No examples provided.

laserscore ~45

The compact one-line reading of a state, without setting or touching a ground.

NameTypeReqDescription
distancenumber––
goalstringyes–
progressstring––

No output schema declared.

No examples provided.

modulate ~118

Check your state AND get the intervention your role should take. Same verdict as check_state, plus a policy decision: whether THIS role returns on THIS drift, and the wording to return with. Pass team + role for a recursion-team preset; without them every drift returns, unstyled. Offline, like everything else here.

NameTypeReqDescription
distancenumber––
goalstringyes–
progressstring––
rolestring–Which role this agent is playing.
teamstring–A recursion-team preset name.

No output schema declared.

No examples provided.

reset_task ~52

Start a genuinely new task. Clears the ground so the next check_state sets a fresh one. Use when the user redirects you — NOT to escape a drift verdict, which is the one thing that makes the reading useless.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

similarity ~46

Token overlap between two statements under the same normaliser the harness uses. Useful for asking whether two goals are the same goal.

NameTypeReqDescription
astringyes–
bstringyes–

No output schema declared.

No examples provided.

Install

How do I install the io.github.degibug-del/laserbrain MCP server?

io.github.degibug-del/laserbrain runs locally as a PyPI package, launched with uvx laserbrain mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

pypi · laserbrain

# add to Claude Code
claude mcp add degibug-del-laserbrain -- uvx laserbrain mcp
Common questions

What is the io.github.degibug-del/laserbrain MCP server?

io.github.degibug-del/laserbrain is an MCP server listed in the public MCP registry as io.github.degibug-del/laserbrain. The drift harness as an MCP server. Offline, no key, a fixed reference an agent checks against. This page covers its PyPI package (laserbrain).

Is the io.github.degibug-del/laserbrain MCP server safe to use?

io.github.degibug-del/laserbrain scores 59 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 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 io.github.degibug-del/laserbrain MCP server expose?

io.github.degibug-del/laserbrain exposes 7 tools: check_state, modulate, reset_task, get_history, similarity, and 2 more. Their descriptions and schemas cost roughly 427 tokens of context every time the server is loaded.

Is the io.github.degibug-del/laserbrain MCP server still maintained?

io.github.degibug-del/laserbrain is still listed as active in the MCP registry. We last reached this channel on 5 November 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 io.github.degibug-del/laserbrain MCP server under?

io.github.degibug-del/laserbrain declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

What did VerifyMCP test on the io.github.degibug-del/laserbrain MCP server?

VerifyMCP ran 14 checks on io.github.degibug-del/laserbrain, covering Known CVEs, Install scripts, Dependency health, Source repository and 10 more. 2 items could not be completed, a gap on our side rather than a finding about io.github.degibug-del/laserbrain: Malware scan and Security disclosure. Endpoint Security and Transport & Reachability do not apply to a PyPI package, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.