io.github.NellInc/saferagenticai-mcp
PYPI · SAFERAGENTICAI-MCP · 2 COMPONENTS
Read-only tools over the Safer Agentic AI framework: 239 patterns + 15 heuristics.
Available components
Last scanned (19 hours ago)
Scores higher than 80% of PyPI servers
Category Security
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- 0 of 29 dependencies flagged as unhealthy. View diagnostics → Pass
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 1 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability74
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 914 tokens (~91/item across 10 items; 10 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management83
- Stability check failed: the tool surface changed between 0.3.6 and 0.4.1: 2 tool removals, 0 breaking changes, 0 additions. See how to fix → Fail
Tool Coverage70
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 9% of tool parameters carry a description.Partial
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 10 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 10 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 4 Nov 26 +15
- Malware scan: unverified → pass ▲ security
- 2 Nov 26 −2
- Stability: pass → fail ▼ security
- Package version: 0.3.6 → 0.4.1 functional
- 1 Nov 26 0
- Stability: 0.97 → pass security
- 31 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- Stability: pass → 0.97 functional
- 29 Oct 26 +15
- Malware scan: unverified → pass ▲ security
- 28 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- 25 Oct 26 0
- Stability: 0.97 → pass security
- 24 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 4 Nov 2026 · Analysed pypi/saferagenticai-mcp@0.4.1
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
| Reason | No attestation published |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 29 packages
| Packages resolved | 29 |
|---|---|
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
find_patterns_for_task ~110
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.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | – |
| task | string | yes | – |
| verbosity | string | – | – |
No output schema declared.
No examples provided.
get_cross_references ~102
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.
| Name | Type | Req | Description |
|---|---|---|---|
| id | string | yes | – |
| include_inferred | boolean | – | – |
No output schema declared.
No examples provided.
get_operational_heuristic ~65
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.
| Name | Type | Req | Description |
|---|---|---|---|
| id | string | yes | – |
No output schema declared.
No examples provided.
get_requirement ~83
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.
| Name | Type | Req | Description |
|---|---|---|---|
| id | string | yes | – |
| include_pattern | boolean | – | – |
No output schema declared.
No examples provided.
get_reverse_references ~55
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.
| Name | Type | Req | Description |
|---|---|---|---|
| id | string | yes | – |
No output schema declared.
No examples provided.
list_operational_heuristics ~123
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.
| Name | Type | Req | Description |
|---|---|---|---|
| query | string | – | Keyword search across titles, principles, narratives |
| suite_id | string | – | Filter by framework suite (e.g., 'D3', 'I2') |
No output schema declared.
No examples provided.
list_requirements ~103
List subgoals matching filters (suite_id, suite_type, content_type, min_confidence, missing_pattern_only). Results capped by limit (default 50, max 100).
| Name | Type | Req | Description |
|---|---|---|---|
| content_type | string | – | – |
| include_pattern | boolean | – | – |
| limit | integer | – | – |
| min_confidence | string | – | – |
| missing_pattern_only | boolean | – | – |
| suite_id | string | – | – |
| suite_type | string | – | – |
No output schema declared.
No examples provided.
list_suites ~43
List all 16 suites in the SaferAgenticAI framework (9 drivers + 7 inhibitors) with subgoal counts and titles. Call this first to orient.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
resolve_id ~73
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'.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | – |
| query | string | yes | – |
No output schema declared.
No examples provided.
search_patterns ~157
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` 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.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | – |
| query | string | yes | – |
| verbosity | string | – | – |
No output schema declared.
No examples provided.
How do I install the io.github.NellInc/saferagenticai-mcp server?
io.github.NellInc/saferagenticai-mcp runs locally as a PyPI package, launched with uvx saferagenticai-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · saferagenticai-mcp
claude mcp add nellinc-saferagenticai-mcp -- uvx saferagenticai-mcp
What is the io.github.NellInc/saferagenticai-mcp server?
io.github.NellInc/saferagenticai-mcp is listed in the public MCP registry as io.github.NellInc/saferagenticai-mcp. Read-only tools over the Safer Agentic AI framework: 239 patterns + 15 heuristics. This page covers its PyPI package (saferagenticai-mcp).
Is the io.github.NellInc/saferagenticai-mcp server safe to use?
io.github.NellInc/saferagenticai-mcp scores 80 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 4 November 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the io.github.NellInc/saferagenticai-mcp server expose?
io.github.NellInc/saferagenticai-mcp exposes 10 tools: list_suites, get_requirement, list_requirements, search_patterns, get_cross_references, and 5 more. Their descriptions and schemas cost roughly 914 tokens of context every time the server is loaded.
Is the io.github.NellInc/saferagenticai-mcp server still maintained?
io.github.NellInc/saferagenticai-mcp is still listed as active in the MCP registry. We last reached this channel on 4 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the io.github.NellInc/saferagenticai-mcp server under?
io.github.NellInc/saferagenticai-mcp declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.