Peecai MCP Server
mcp-server-peecai
npm
v1.3.0
Source verified
Published by thein-art — publish provenance cryptographically ties this package to that repository. That is proof of origin, not an official vendor package.
Community MCP server for the Peec AI API - AI Search Analytics
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 0 = 100. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
✓ No adoption-risk deductions — minimal blast radius, verified enough, and fully inspected.
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Findings 0
Tools 38
Each tool and what it can reach — statically extracted from the published source.
accept_brand_suggestionno sensitive capabilityaccept_prompt_suggestionno sensitive capabilityaccept_topic_suggestionno sensitive capabilitycreate_brandno sensitive capabilitycreate_promptno sensitive capabilitycreate_tagno sensitive capabilitycreate_topicno sensitive capabilitydelete_brandno sensitive capabilitydelete_promptno sensitive capabilitydelete_tagno sensitive capability
Show 28 more tools ↓
delete_topicno sensitive capabilityget_brands_reportno sensitive capabilityget_chat_contentno sensitive capabilityget_domains_reportno sensitive capabilityget_project_profileno sensitive capabilityget_url_contentno sensitive capabilityget_urls_reportno sensitive capabilitylist_brand_suggestionsno sensitive capabilitylist_brandsno sensitive capabilitylist_chatsno sensitive capabilitylist_model_channelsno sensitive capabilitylist_modelsno sensitive capabilitylist_projectsno sensitive capabilitylist_prompt_suggestionsno sensitive capabilitylist_promptsno sensitive capabilitylist_tagsno sensitive capabilitylist_topic_suggestionsno sensitive capabilitylist_topicsno sensitive capabilityreject_brand_suggestionno sensitive capabilityreject_prompt_suggestionno sensitive capabilityreject_topic_suggestionno sensitive capabilitysearch_queriesno sensitive capabilityset_project_profileno sensitive capabilityshopping_queriesno sensitive capabilityupdate_brandno sensitive capabilityupdate_promptno sensitive capabilityupdate_tagno sensitive capabilityupdate_topicno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (38 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 1
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v1.3.0 latest |
A 100/100 | 0 | 1.13.0 | 2026-09-07 |
Embed this score
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
Verify this score yourself
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
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