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io.github.NellInc/saferagenticai-mcp

io.github.NellInc/saferagenticai-mcp · v0.3.6

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

MCPremotelocal · pypino credentials

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Last check

Reachable, 10 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

A 88/100

What it does: 10 tools · 10 read, 0 write

Test call list_suites: worked (1,015 ms)

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +6
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: +2
  • Read/write annotations: +5
  • Safe test call: +20
  • More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL
https://mcp.saferagenticai.org/mcp
Package
registry:   pypi
identifier: saferagenticai-mcp
version:    0.3.6
transport:  stdio

Tools

10 tools listed at last check
  • list_suites List all 16 suites in the SaferAgenticAI framework (9 drivers + 7 inhibitors) with subgoal counts and titles. Call this first to orient.
  • get_requirement 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.
  • list_requirements List subgoals matching filters (suite_id, suite_type, content_type, min_confidence, missing_pattern_only). Results capped by limit (default 50, max 100).
  • search_patterns Field-weighted keyword search across the framework. Terms match at word starts on lowercased text and are IDF-weighted, so rare terms outrank ubiquitous ones; field weights: title 10x, summary 4x, SFR text 3x (all of a subgoal's SFRs scored as one field), description 2x, pattern body 1x. `matched_in
  • get_cross_references 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 'ne
  • resolve_id 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'.
  • find_patterns_for_task 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
  • get_reverse_references 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.
  • list_operational_heuristics 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 (k
  • get_operational_heuristic 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.

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