polygraph

A system for assigning A–F behavioral safety grades to MCP servers, which are services that provide extra tools to AI agents. It probes the server’s tools and publishes reproducible evidence about the tested version.

In plain words
What is it for?
It helps look up grades, verify published attestations, request a new evaluation, and understand the evidence behind a grade.
Why use it?
It gives developers a way to inspect a server’s behavior before using it, while making clear that a passing grade is not a guarantee of safety.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/polygraphso/litmus/polygraph
Any agent
npx skills add polygraphso/litmus --skill polygraph
Clone the repo
git clone --depth 1 https://github.com/polygraphso/litmus

Made for: Claude Code, Codex.

Per session 225 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,348 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00225 $0.03348
Opus 5 $0.00112 $0.01674
Sonnet 5 $0.00045 $0.00670
Haiku 4.5 $0.00022 $0.00335

Measured yesterday against content hash 3ab06611b465, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

polygraph scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/polygraph/skills/polygraph/SKILL.md · 246 lines

How it starts

The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Polygraph: Behavioral Trust Grades for MCP Servers

Agents wire up third-party MCP servers and then trust whatever those servers' tools return. Polygraph tests an MCP server's behavior before your agent does, and assigns a letter grade A–F backed by reproducible evidence.

A passing grade is a measurement, not a guarantee — it says "this exact tool surface did not misbehave under these probes," and because the harness is open and deterministic, anyone can re-run it and disprove a bad grade. That falsifiability is the whole point.

  • Home / methodology: polygraph.so
  • Lookup CLI (npm): polygraphso
  • Grading harness: @polygraphso/litmus (open source)

What a grade measures

Polygraph connects to a server the way an agent would — stdio for local packages, Streamable HTTP for remote URLs — fingerprints its exact tool surface (tools/list → canonical JSON → sha256 → bytes32), then runs four probe categories:

  • C-01 — Tool-output injection. Does the server try to hijack the agent? Static scan of tool names/descriptions/schemas for injection-shaped content (invisible unicode, instruction mimicry, markdown tricks) plus dynamic bait calls that check whether tool outputs smuggle in instructions.
  • C-02 — Permission / egress overreach. Does the server do more than it claims? Flags tools that declare readOnlyHint: true but carry destructive verbs, and runs the server in a hardened default-deny Docker sandbox where any outbound network attempt is a finding.
  • C-03 — Sensitive-data handling. Does the server leak secrets? Plants canary values in the environment and working directory, exercises the tools, and scans both tool outputs and egress for any canary that surfaces.
  • C-04 — Adversarial-input handling. Does the server stay robust under hostile input? Runs two probes on non-state-changing tools, with no Docker required: stress-tests each tool with malformed and oversized inputs (fails if the server crashes, hangs, or leaks an uncaught stack trace — a clean validation error or benign result passes); and feeds jailbreak-pattern strings and scans the server's outputs with the C-01 injection scanners, failing only if the server emits injection-shaped content it did not merely reflect from the input (a verbatim echo is excluded). A C-04 failure caps the overall grade at D.

Read the full file on GitHub · 246 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 246 lines · 225 tokens per session scan A 3ab06611b465

Subscribe to this mod's changes

polygraph is a skill published in the GitHub repository polygraphso/litmus (8 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 225 tokens to every session and 3,348 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.