Srdcheck MCP server

srdcheck

A shared rules rail for agents: named, cited checks with explicit boundaries, so every caller can use the same deterministic result without mistaking a partial check for global legality.

Machine verdicts over specific rules of the System Reference Document 5.2.1: cited when a rule is applied, reproducible, offline, and honest enough to refuse questions outside the shipped scope. The rules lawyer for agents — including an agent acting as the authorized DM.

Agents start here → SKILL.md — the front door: when to call this, worked examples, MUST/MUST NOTs. Family contract: FAMILY.md.

Status: v0.9.0 alpha — young but real, building in the open. The kill tests that shaped the product — including the one that killed half our original idea — are in eval/RESULTS-phase0.md; the with/without-rails demo is in demo/mage-hand/; the truth scorecard below is generated by CI.

Runtime and operating-system guarantees are defined in the support matrix: Python 3.10–3.13, a full Ubuntu suite, and explicit installed-artifact smoke contracts on Windows and macOS.

Why this exists

A game increasingly runs not as one model but as several agents sharing one evolving state — a GM, player agents, a rules referee, tool-callers. The moment more than one mind adjudicates, the binding problem stops being any single agent's knowledge or attention budget and becomes consistency: five capable models will each read the SRD and rule on grapple, concentration, or a death save a little differently, and the shared game state quietly desyncs. No amount of individual intelligence guarantees they agree with each other, and every re-derivation is another chance to drift. The fix is a deterministic rail they all call — the same atoms, the same citations, the same verdict every time — so every applied-rule result carries one provenance any agent (or a human) can audit. Table rulings retain separate ruling lineage. That is where srdcheck stops being a convenience and becomes load-bearing.

Even at a table of one, the rail earns its place. A model running a game is a brilliant improviser with a finite attention budget: every mechanical micro-check it handles in-context — is this legal, is that slot spent, does the reaction refresh this round — spends tokens and attention that belong to the only work that needs a mind, the story. And the checks a model can answer, it cannot prove, cannot reproduce, and — as our own benchmark showed — will not refuse when the question is outside the rules' jurisdiction.

We tested this before building. Frontier models answered our SRD rules questions nearly perfectly — and confidently ruled on house rules, GM discretion, and content that doesn't exist in the SRD, where the only correct answer is "not my call." Small local models got 19–30% wrong with zero refusals. So srdcheck does not compete with what models know. It is a rail: structured facts in, a deterministic scoped result out, with citations whenever it applies a rule — and the same rail for every agent at the table.

What it is

srdcheck answers named, bounded questions such as: does this proposal pass the modeled action-economy check? and which modeled budget option kinds remain? See the generated capability and claim map for the canonical checked and unchecked scope of every tool.

Shortened. The full README is on GitHub.