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Quill MCP server

by manumarri-sudo·io.github.manumarri-sudo/quill·v0.2.0a5

Pre-execution gate for AI-agent tool calls. Touch ID approval. Tamper-evident audit log.

A85/100grade A
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Safety scan
A85/100

full report

Adoption
New

0 stars18 downloads/wk

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If you have run it, two minutes of your experience saves the next person an afternoon.

Quill tools

No tool declarations could be read from the package source. They show once the server is installed.

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

1 medium
  • Code scan55 source files scanned20/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 6 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Findings (1)

  • mediumsubprocess with shell=Trueexec.shell-true
    quillx-0.2.0a5/experiments/vibe_coder_harness.py: … = subprocess.run( command, shell=True, cwd=SANDBOX_DIR, capture_output=True, …
Overall 85/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Quill compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
85/100
higher than 73% of 4,460 AI and agents servers
Downloads a week
18
more than 5% of 1,538 AI and agents servers with a package

Install Quill in Claude Code, Cursor or VS Code

claude mcp add quill -- uvx quillx
Add to Cursor

What the publisher says

From the Quill repository's README, as published. We do not edit it. Read it on GitHub

notari

Notari issues a signed Change Passport for every AI-authored pull

request: a receipt any reviewer or auditor can re-verify from the signature

alone, without re-running Notari or trusting a screenshot, recording which

files a human approved the agent to touch and

whether it stayed inside them. A human signs the boundary once; in CI, Notari

checks each pull request against it and stamps the passport PASS,

NEEDSREVIEW, or BLOCK**. There is no model in that verdict, so it cannot

be prompt-injected. It does not judge whether the code is correct: it

attests to where the change went and whether it leaked a secret, the part a

human most often skims past on a large agent PR. Alpha; treat

the security model

as the source of truth over any one-line claim.

Start here: one command

uvx notari init

Nothing to install first. In one command, inside any git repo, that generates an approver keypair and a gate keypair, signs a secure-by-default perimeter, writes the hardened GitHub workflow (pullrequesttarget, SHA-pinned, the pull request checked out into a data-only directory), gitignores your private keys, and then prints your honest posture plus the exact steps still missing. Measured from a clean machine with no Python tooling configured, the CLI resolves and runs in about a second and a half.

Prefer a persistent install? pipx install notari or pip install notari, then notari init. Either way the next two commands are the whole daily loop:

notari begin "add rate limiting" --scope "src/api/**"    # sign what the agent may touch
notari verify --strict                                    # in CI: PASS, NEEDS_REVIEW, or BLOCK

notari init automatically forbids directories that look sensitive (auth,

migrations, infra, terraform, deploy, and similar). Forbidden beats contract

scope, so scoping a task into one of them returns BLOCK by design. When you really

do need to touch one, set the boundary explicitly and sign it:

notari guard --key approver.pem --allow "src/" --forbid "migrations/".

What you actually get

Four surfaces, each stated at its real strength rather than its most flattering one:

1. The gate, which is the provable boundary. In CI, outside the agent's reach, every changed path outside .notari/ is measured against a signed scope and a signed perimeter, each touched file is scanned for 26 vendor secret patterns, and renames (both endpoints), mode-only changes, binaries, symlinks, submodules, and .gitattributes diff-hiding are all in the inventory rather than blind spots. You name the scope per task (--scope), so a narrow scope means "only these paths", and the explicit --scope '**' means "anything the signed perimeter does not forbid", stated plainly on the passport either way so a PASS is never ambiguous. Secret detection is a finite pattern set, so it catches the common vendor-format leaks rather than proving no secret exists. There is no model in the decision path, so there is nothing to prompt-inject.

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Quill: common questions

Is Quill MCP server safe?
Yes, by our scan: it is graded A (85/100). Read the Quill safety report
How do I install Quill?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Quill need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is Quill maintained?
The last commit was 44 days ago (2026-09-21). The latest release is v0.2.0a5.
What can I use instead of Quill?
Servers from other publishers that do the same job: three.ws Provenance MCP server, HOL Guard MCP server and Decionis MCP server.
How does Quill compare with other AI and agents MCP servers?
safety score 85/100 (higher than 73% of 4,460 AI and agents servers); downloads a week 18 (more than 5% of 1,538 AI and agents servers with a package). Full comparison.

Alternatives to Quill

Same job from other publishers: the closest match first, then the best rated.

  • three.ws Provenance
    Append-only, signed, on-chain-verifiable agent action log — record and audit what agents did.
    B
  • HOL Guard
    Local-first AI agent security evidence and approval workflows through HOL Guard's stdio MCP server.
    A
  • Decionis
    Authorize consequential AI agent actions before execution
    A
  • Emilia Protocol
    Exact-action approval for consequential agent actions: request, track, and verify signed receipts.
    B
  • Roast My Design System
    Audit your Design System and serve your Agent the rules that keep AI-written UI on-system.
    A