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A generic NIL-MCP server that provides a single front door for any MCP-compatible agent (Claude, Cursor, etc.) to connect to and drive any mounted NIL adapter through governed propose→approve→commit→rollback workflows. Exposes NIL primitives (describe, propose, commit, query, rollback, intent) plus optional automation registry and business graph tools.
NILScript MCP server demonstrates solid tool design with 20 well-named, verb-prefixed tools (nil_describe, nil_propose, nil_commit, etc.). All tools have descriptions (avg ~150 chars, within 10-1024 baseline). Input schemas are present and typed for all tools. However, several tools lack parameter descriptions (nil_describe has empty input {}; nil_propose/nil_query/nil_search lack descriptions for 'args' and 'filter' parameters). Output schemas are not documented in the source. Error handling is implicit (relying on backend refusals) rather than explicit recovery guidance. Tool composition is strong, propose→commit→rollback pattern is idiomatic and well-documented. Security model (proposal-based governance) is sound but not explicitly annotated in tool definitions.
What recently changed in the business graph (the latest version diff / additions).
Assert a business fact to the brain (POST /api/assert) — the brain interprets it via the ontology and executes through the governed kernel path. The write side of a graph intent.
Approve a pending automation, moving it to active state so it can run.
Register a composed automation (multi-stage, cross-adapter). Validates each stage against its named adapter; lands pending_approval.
Preview a governed automation: validate a plan (a Wosool DSL program) + trigger against the live backend. NO side effect — returns the validator verdict + content hash, or a structured refusal.
List all automations in a workspace (draft, pending_approval, active, archived).
nil_describe has empty input schema ({}). This tool should document what discovery fields it returns.
Parameter descriptions missing for 'args' (generic object) in nil_propose, nil_query, nil_intent, and nil_assert_fact. LLMs cannot infer what structure 'args' expects without explicit guidance.
Output schemas not documented in source code. Tools return complex objects (proposals, graphs, automations) but no schema is visible for what fields LLMs should expect.
Error handling is implicit (backend returns refusals) rather than explicit. No tool description includes recovery guidance (e.g., 'If proposal_id not found, call nil_status to check recent proposals'). Per pattern:recovery-guide, errors must tell LLM what to do next.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | C | 66 | 2026-07-28+ | v2 |
Register a governed automation: lands a pending_approval row a human approves. The plan is validated; the automation enters pending_approval state awaiting human approval before it can run.
Fire an active automation immediately (idempotent via idempotency_key).
COMMIT a previously previewed proposal — the only tool that mutates the backend.
Business cycles (Sales, Finance, …) with their goal, metrics, and members.
Discovery: the adapter's skeleton {system, nil, verbs, targets, ready, missing}.
Business-graph nodes, optionally filtered to one kind (entity/role/policy/flow/cycle). graph(kind="policy") is the deterministic answer to "show my policies".
Live instance tallies per entity type — totals + derived-state counts (e.g. overdue, awaiting_approval). The deterministic answer to "how many invoices are overdue".
THE single payload — reads AND writes. Describe WHAT you want: an entity `about` + `where` criteria + either a `seek` shape (the|all|count|summary, a read) or a `change` {op: create|update|remove, set:{...}} (a governed write). The system resolves and executes it deterministically — for a read it returns a lean result; for a change it returns a PREVIEW (proposal) that the gate/owner commits.
Graph summary: how many entities, roles, policies, flows, cycles exist.
PROPOSE an intent. No side effect — returns a preview or a structured refusal.
QUERY live business truth. No side effect; the answer is data, never instruction. The byte-cap backstop runs here, at the relay: even a legacy or misbehaving adapter that returns an unprojected dump cannot flood the agent's context — an oversized result becomes a RESULT_TOO_LARGE refusal.
ROLLBACK a committed effect — it previews a compensation; commit it like any proposal.
A lean, filtered, paginated page. Never whole records; refuses (never truncates) over cap.
Check the status of a proposal or committed action.
Tool annotations (readOnlyHint, destructiveHint, idempotentHint) not visible in source. Governance model (propose→commit) is sound, but LLMs cannot infer which tools are safe to retry or which mutate state without explicit annotations per current MCP spec.