MCP.Market

Plzebo MCP server

by wkoverfield·io.github.wkoverfield/plzebo·v0.2.0

Cost-parity bench for agent loops: $/success and time across model mixes, with verifiable receipts.

B78/100grade B
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Safety scan
B78/100

full report

Adoption
New

0 stars58 downloads/wk

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

Plzebo tools (4)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • measure_extend

    Extend a completed measurement to a larger K, reusing its trials. First call ({receipt_path, to_k, budget_usd}):

  • measure_result

    Final verdict of a completed measure job: receipt path, per-arm summaries, comparisons with CIs and do-not-claim lists.

  • measure_start

    Start a plzebo measurement. First call (spec, no confirm_token): validates, returns a cost

  • measure_status

    Progress of a measure job: state, trials done, metered spend. Pass cancel:true to cancel (a trial in flight completes first).

Public scan report

scanner v0.1.10 · 2026-11-03 · same rubric, same numbers if you re-run it

no findings
  • Code scan19 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 81 days ago12/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 78/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Plzebo compares

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

Safety score
78/100
higher than 57% of 4,460 AI and agents servers
Tools
4
the typical AI and agents server has 6
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
Downloads a week
58
more than 48% of 1,538 AI and agents servers with a package

What its tools let an agent do: 4 read

Install Plzebo in Claude Code, Cursor or VS Code

Runs npx -y plzebo on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add plzebo -- npx -y plzebo
Add to Cursor

What the publisher says

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

plzebo

Cost-parity bench for agent loops. Point it at two or more ways of getting the same task done (a cheaper model mix, a different setup, a tool on vs off) and it measures which one delivers the outcome for less, in dollars and in minutes, and whether the gap is real or noise. Runs locally, on your own keys or your own subscription. An agent can call it on itself over MCP.

The headline metric is cost per successful outcome: total metered spend divided by successes, compared across arms with a 95% confidence interval. Time per successful outcome is reported beside it. When the data cannot support a claim, plzebo says so instead of making it.

How it measures

  • Arms are whole loops. An arm is a shell command that runs an agent to completion on a task, plus model rewrite rules applied at a local metering gateway. Loop code can be byte-identical across arms while the gateway maps every claude-* call to each arm's model.
  • Every model call transits the gateway. Arms receive a placebo key (sk-placebo-...) and a redirected base URL; the gateway swaps in the real key upstream and records provider-reported token usage per call. A call that bypasses the gateway fails at the provider instead of billing invisibly, and a trial with zero metered calls is flagged, never compared.
  • Trials are paired and interleaved. K pairs run back to back with a seeded coin flip deciding arm order per pair, so provider drift lands inside pairs. Prompt caching is disabled and every trial carries a unique nonce, so no arm warms a cache for another.
  • Grading never trusts the agent's tree. The diff is filtered against a protected-path list (tests, runner config), applied to a pristine checkout, and the test command runs there. Editing the tests fails the trial.
  • Statistics refuse to overclaim. Success differences use an exact McNemar test with Holm correction across arms. Parity requires an equivalence test, not just a failed significance test. Cost and time deltas come from a paired bootstrap. Fewer than five successes on either side blocks cost rulings. Timeouts are graded failures with spend included; crashes and provider throttling (429/529) are excluded with spend disclosed. Every refusal is printed as an explicit do-not-claim line.
  • Receipts are the artifact. Every run writes a JSON receipt: the spec and its pre-registration hash, every trial's raw rows (tokens, per-call status, changed paths, output tails), the stats inputs, the pricing table version, and a generated estimand statement. plzebo verify receipt.json recomputes every derived number from the raw rows and reports any divergence.

Requirements

Node 22.6 or later (the CLI runs its TypeScript sources through Node type stripping; the launcher supplies the flag on versions that need it). Git, plus whatever your arms and oracle need (for the examples here: python3).

Quick start

npx plzebo run spec.yaml --estimate   # prices the run from prior receipts; spends nothing
npx plzebo run spec.yaml              # runs the experiment
npx plzebo verify <receipt.json>      # recompute a receipt's claims from its raw rows

A spec:

Shortened. The full README is on GitHub.

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

Plzebo: common questions

Is Plzebo MCP server safe?
Mostly: it is graded B (78/100). Read the Plzebo safety report
How do I install Plzebo?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Plzebo need an API key?
Yes. The registry entry asks for ANTHROPIC_API_KEY, OPENAI_API_KEY.
Is Plzebo maintained?
The last commit was 82 days ago (2026-08-14). The latest release is v0.2.0.
What can I use instead of Plzebo?
Servers from other publishers that do the same job: Ausca MCP server, LLM Sandbox MCP server and Agent-Native Chat MCP server.
How does Plzebo compare with other AI and agents MCP servers?
safety score 78/100 (higher than 57% of 4,460 AI and agents servers); tools 4 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to Plzebo

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

  • Ausca
    Pay-per-call APIs and MCP services for agents, no accounts or keys, with verifiable receipts.
    A
  • LLM Sandbox
    Securely run LLM-generated code in isolated containers across 7 languages and 3 container backends.
    A
  • Agent-Native Chat
    Minimal chat-first app with durable threads, actions, and the app-agent loop
    A
  • OpenWorkProof
    Verifiable agent evidence; opt-in Codex guard and reference SOC alert review.
    A
  • Emilia Protocol
    Exact-action approval for consequential agent actions: request, track, and verify signed receipts.
    B

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