Wechat Mp MCP Server
@xihe-lab/wechat-mp-mcp-server
npm
v0.1.2
Published by @xihe-lab — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
WeChat MP (Media Platform) MCP Server for managing articles, drafts and media via AI assistants
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 − 7 = 93. 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:
| Points | Adoption-risk factor |
|---|---|
| −6 | capability blast radius (high) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
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 1
high Dynamic code execution in server code (dist/index.js)MTC-SRC-001
In the server's implementation (`dist/index.js:10833`): Evaluating strings as code is the most direct RCE primitive; if any tool input reaches it, the server executes attacker-chosen code. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: s(l, t)); const y = new Function(`${jt.default.self}`, `${jt.default.scope}`, l)(this, this.scope.get()); if (th
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server dist/index.js
Tools 14
Each tool and what it can reach — statically extracted from the published source.
wechat_auth_get_tokenreads sensitive datawechat_auth_configureno sensitive capabilitywechat_auth_refreshno sensitive capabilitywechat_draft_addno sensitive capabilitywechat_draft_deleteno sensitive capabilitywechat_draft_getno sensitive capabilitywechat_draft_listno sensitive capabilitywechat_material_upload_imageno sensitive capabilitywechat_media_getno sensitive capabilitywechat_media_uploadno sensitive capability
Show 4 more tools ↓
wechat_publish_deleteno sensitive capabilitywechat_publish_getno sensitive capabilitywechat_publish_listno sensitive capabilitywechat_publish_submitno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (14 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 |
|---|---|---|---|---|
v0.1.2 latest |
A 93/100 | 1 | 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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