saferagenticai-mcp
Read-only tools over the Safer Agentic AI framework: 238 patterns + 14 heuristics.
¿Debería usar esto?
Calidad y seguridad
Hallazgos (1)
- LOWen get_cross_references
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.
Instalar
Instalación con un clic
Agrega esto a tu archivo `claude_desktop_config.json`:
{
"mcpServers": {
"saferagenticai-mcp": {
"command": "uvx",
"args": [
"saferagenticai-mcp"
]
}
}
}Paquetes ejecutables
0.3.6stdioPuntos de conexión remotos
https://mcp.saferagenticai.org/mcpstreamable-httpQué puede hacer
Inventario de herramientas
Herramientas (12)
🟢list_suites
List all 16 suites in the SaferAgenticAI framework (9 drivers + 7 inhibitors) with subgoal counts and titles. Call this first to orient.
Esquema de entrada
{
"type": "object",
"properties": {},
"additionalProperties": false
}🟢get_requirement(id, include_pattern)
Retrieve one subgoal (framework normative content + Pattern layer guidance) by pattern_id (e.g., 'D3::idx2::sandboxing') or display_id (e.g., 'D3.2'). display_id may resolve to multiple subgoals — underlined variants share display_ids.
Esquema de entrada
{
"type": "object",
"properties": {
"id": {
"type": "string",
"maxLength": 500
},
"include_pattern": {
"type": "boolean",
"default": true
}
},
"required": [
"id"
],
"additionalProperties": false
}🟢list_requirements(suite_id, suite_type, content_type, min_confidence, missing_pattern_only, ...)
List subgoals matching filters (suite_id, suite_type, content_type, min_confidence, missing_pattern_only). Results capped by limit (default 50, max 100).
Esquema de entrada
{
"type": "object",
"properties": {
"suite_id": {
"type": "string",
"maxLength": 500
},
"suite_type": {
"type": "string",
"enum": [
"driver",
"inhibitor"
]
},
"content_type": {
"type": "string",
"enum": [
"code-applicable",
"governance",
"process",
"ecosystem"
]
},
"min_confidence": {
"type": "string",
"enum": [
"low",
"medium",
"high"
]
},
"missing_pattern_only": {
"type": "boolean"
},
"include_pattern": {
"type": "boolean",
"default": false
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 100,
"default": 50
}
},
"additionalProperties": false
}🔴search_patterns(query, limit, verbosity)
Field-weighted keyword search across the framework. Substring match on lowercased terms; field weights: title 10x, summary 4x, SFR text 3x, description 2x, pattern body 1x. `matched_in` reports the highest-weighted field that matched. No semantic / embedding search — known limitation, see /mcp.html. Use verbosity='compact' to drop snippets and confidence flags (~70% smaller payload) when triaging.
Esquema de entrada
{
"type": "object",
"properties": {
"query": {
"type": "string",
"minLength": 2,
"maxLength": 500
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 50,
"default": 10
},
"verbosity": {
"type": "string",
"enum": [
"compact",
"full"
],
"default": "full"
}
},
"required": [
"query"
],
"additionalProperties": false
}🟢get_cross_references(id, include_inferred)
Return outgoing adjacencies for a pattern. `explicit_cross_references` are author-asserted (each pattern's `cross_references` YAML field). `inferred_adjacent` (when include_inferred=true) currently returns *same-suite siblings only* — it does not do semantic similarity. Treat inferred entries as 'neighbours worth scanning,' not as endorsed dependencies.
Esquema de entrada
{
"type": "object",
"properties": {
"id": {
"type": "string",
"maxLength": 500
},
"include_inferred": {
"type": "boolean",
"default": true
}
},
"required": [
"id"
],
"additionalProperties": false
}🟢resolve_id(query, limit)
Resolve a loose reference (partial id, display_id, slug fragment, or title keyword) to canonical pattern_id(s). Call this when you have a rough reference and need the exact id before calling get_requirement. Always returns candidates — never 'not found'.
Esquema de entrada
{
"type": "object",
"properties": {
"query": {
"type": "string",
"minLength": 1,
"maxLength": 500
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 20,
"default": 5
}
},
"required": [
"query"
],
"additionalProperties": false
}🟢find_patterns_for_task(task, limit, verbosity)
Given a natural-language task description (e.g., 'I'm building a tool-using agent that runs shell commands'), return the most relevant patterns grouped by suite. Use this as a starting point for any cross-cutting design question; then follow up with get_requirement on specific pattern_ids. Defaults to verbosity='compact' (cheap triage); pass 'full' to inline snippets and confidence flags.
Esquema de entrada
{
"type": "object",
"properties": {
"task": {
"type": "string",
"minLength": 5,
"maxLength": 500
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 25,
"default": 8
},
"verbosity": {
"type": "string",
"enum": [
"compact",
"full"
],
"default": "compact"
}
},
"required": [
"task"
],
"additionalProperties": false
}🟢list_unreviewed(limit)
Return patterns that have not been human-reviewed yet (no reviewed_by). Sorted low-confidence first, then needs_human_review flagged, then alpha. Use during Phase 3 review to pick the next pattern to examine.
Esquema de entrada
{
"type": "object",
"properties": {
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 250
}
},
"additionalProperties": false
}⚪review_stats
Coverage stats: total patterns, reviewed %, per-suite and per-confidence breakdown. Surfaces load-time validation issue count.
Esquema de entrada
{
"type": "object",
"properties": {},
"additionalProperties": false
}🟢get_reverse_references(id)
Return patterns that reference the given pattern_id in their cross_references. Complement to get_cross_references (outgoing); this shows incoming. Use to find all consumers of a given pattern.
Esquema de entrada
{
"type": "object",
"properties": {
"id": {
"type": "string",
"maxLength": 500
}
},
"required": [
"id"
],
"additionalProperties": false
}🟢list_operational_heuristics(suite_id, query)
List operational heuristics distilled from production agentic AI deployment (Claude Code, Rewind). These are cross-cutting safety principles discovered through building and operating AI agents, mapped to framework suites. Optional filters: suite_id (heuristics relevant to a specific suite), query (keyword search across titles and principles). Separate from the normative pattern layer — different category of knowledge.
Esquema de entrada
{
"type": "object",
"properties": {
"suite_id": {
"type": "string",
"maxLength": 500,
"description": "Filter by framework suite (e.g., 'D3', 'I2')"
},
"query": {
"type": "string",
"maxLength": 500,
"description": "Keyword search across titles, principles, narratives"
}
},
"additionalProperties": false
}🟢get_operational_heuristic(id)
Retrieve a single operational heuristic by id (e.g., 'OH::geoffrey-pattern'). Returns the full entry: principle, framework mapping, evidence sources from production deployment, design patterns, anti-patterns, and discovery narrative.
Esquema de entrada
{
"type": "object",
"properties": {
"id": {
"type": "string",
"maxLength": 500
}
},
"required": [
"id"
],
"additionalProperties": false
}Comunidad
Evidencia