bots.st/saferagenticai-mcp
saferagenticai-mcp
Find patterns and heuristics for tasks
4731 ms
answered our call
- State
- Answered
- Protocol
- MCP 2025-06-18
- Tools listed
- 10
- Answered
- 3 of the last 3 calls
How to reach it
- MCP, HTTP
https://mcp.saferagenticai.org/mcp - PyPI
uvx saferagenticai-mcpReleased 6 Nov 2026, version 0.4.2
What it can do
| Tool | What it says it does |
|---|---|
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… |
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… |
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. |
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. |
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… |
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). Every pattern is a model-generated draft (review_status generated_draft; there is no human-review process); confidence is the drafting model's… |
list_suites | List all 16 suites in the SaferAgenticAI framework (9 drivers + 7 inhibitors) with subgoal counts and titles. Call this first to orient. |
resolve_id | Resolve a loose reference (partial id, display_id, slug fragment, or title keyword) to canonical pattern_id(s). Case, separator and G/I prefix are normalised (d2.1, D2-1, 'D2 1', G1.2); a hyphen or space returns both the numbered requirement and its underlined variant. Call this when you have a… |
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… |
In its maker's words
Read-only tools over the Safer Agentic AI framework: 239 patterns + 15 heuristics.
- Source
- github.com/NellInc/saferagenticai-mcp
- Publisher
- NellInc (2 listings in the registry)
- Listed from
- the official MCP Registry as
io.github.NellInc/saferagenticai-mcp - Version
- 0.4.2, updated 6 Nov 2026
- Kinds of work
- AI models and agent tools, Search and research, Writing and translation
The domain it lives on
- saferagenticai.org
- registered 24 Sep 2024 (2 years ago), at GoDaddy.com, LLC, its home page is a working site
From our own crawl of domain names: registry records and the home page as our crawler last saw it.
Every call we made
| When | What happened | Time |
|---|---|---|
| Answered | 4731 ms | |
| Answered | 4577 ms | |
| Answered | 2185 ms |
Next door
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