saferagenticai-mcp

Read-only tools over the Safer Agentic AI framework: 238 patterns + 14 heuristics.

使うべきか

品質と安全性

A
説明の品質
96%
スキーマの完全性
71%
命名の品質
98%
ポイズニングのリスク
100%
権限の一致
100%
プロトコルへの準拠
100%

検出事項(1)

  • LOWTool 'get_cross_references' description lacks action verbget_cross_references 内

ツール定義とプロトコルへの準拠に関する自動分析に基づいています。

コンテキストコスト

~1,408トークン数(ツール定義)
~584 B一般的なレスポンスサイズ
注意への影響は中程度(128k コンテキストの 1.10%)

これは、サーバーのツールがモデルのコンテキストに読み込まれるたびに消費されるおおよそのトークン数です。数が多いほど、ほかのタスクに使える注意が減ります。

インストール

ワンクリックインストール

これを `claude_desktop_config.json` ファイルに追加してください:

{
  "mcpServers": {
    "saferagenticai-mcp": {
      "command": "uvx",
      "args": [
        "saferagenticai-mcp"
      ]
    }
  }
}

実行可能なパッケージ

pypisaferagenticai-mcp0.3.6stdio

リモートエンドポイント

https://mcp.saferagenticai.org/mcpstreamable-http

できること

ツール一覧

ツール(12)

🟢 読み取り専用🟡 書き込み🔴 削除⚪ 不明
🟢list_suites

List all 16 suites in the SaferAgenticAI framework (9 drivers + 7 inhibitors) with subgoal counts and titles. Call this first to orient.

入力スキーマ

{
  "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.

入力スキーマ

{
  "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).

入力スキーマ

{
  "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.

入力スキーマ

{
  "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.

入力スキーマ

{
  "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'.

入力スキーマ

{
  "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.

入力スキーマ

{
  "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.

入力スキーマ

{
  "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.

入力スキーマ

{
  "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.

入力スキーマ

{
  "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.

入力スキーマ

{
  "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.

入力スキーマ

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "maxLength": 500
    }
  },
  "required": [
    "id"
  ],
  "additionalProperties": false
}

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検証済みバージョンは記録されていませんツール 12 件
検証済みバージョンは記録されていませんツール 12 件