Directive Run MCP Server
@directive-run/mcp
npm
v0.6.28
Published by @directive-run — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
Model Context Protocol server that exposes Directive to AI clients — knowledge files, code examples, and Claude Code skill bundles today, with room to grow into runtime introspection and tooling. stdio for local clients (Claude Desktop, Cursor, MCP Inspec
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 4 = 96. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −3 | capability blast radius (moderate) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Findings 0
Tools 22
Each tool and what it can reach — statically extracted from the published source.
get_exampleingests untrusted inputget_knowledgeingests untrusted inputget_migration_patterningests untrusted inputget_package_infoingests untrusted inputget_review_ruleingests untrusted inputget_skillingests untrusted inputfix_codeno sensitive capabilitygenerate_moduleno sensitive capabilityget_composable_packagesno sensitive capabilityget_server_infono sensitive capability
Show 12 more tools ↓
list_examplesno sensitive capabilitylist_knowledgeno sensitive capabilitylist_migration_sourcesno sensitive capabilitylist_module_sectionsno sensitive capabilitylist_packagesno sensitive capabilitylist_review_rulesno sensitive capabilitylist_skillsno sensitive capabilityplayground_linkno sensitive capabilityreview_sourceno sensitive capabilityrun_in_sandboxno sensitive capabilitysearch_examplesno sensitive capabilitysearch_knowledgeno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (22 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 10
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v0.6.28 latest |
A 96/100 | 0 | 1.13.0 | 2026-09-07 |
v0.6.26 |
A 96/100 | 0 | 1.13.0 | 2026-09-01 |
v0.6.23 |
A 96/100 | 0 | 1.12.1 | 2026-08-21 |
v0.6.22 |
A 96/100 | 0 | 1.12.1 | 2026-08-20 |
v0.6.21 |
A 96/100 | 0 | 1.12.1 | 2026-08-19 |
Show 5 more versions ↓
v0.6.19 |
A 96/100 | 0 | 1.12.1 | 2026-08-18 |
v0.6.18 |
A 96/100 | 0 | 1.12.1 | 2026-08-16 |
v0.6.13 |
A 96/100 | 0 | 1.12.1 | 2026-08-15 |
v0.6.9 |
A 96/100 | 0 | 1.12.1 | 2026-08-14 |
v0.6.8 |
A 96/100 | 0 | 1.12.1 | 2026-08-13 |
Embed this score
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
Verify this score yourself
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
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