AuditSocials Compliance MCP
OfficialChicks ad copy against Google Ads advertising policies, flagging potentially violating phrases and suggesting compliant alternatives.
Checks AI-generated social media and ad content against Meta's (Facebook/Instagram) advertising and community policies for compliance, identifying risky phrases, severity, and providing compliant rewrites.
Chicks content against Pinterest's advertising and community policies, flagging risky phrases and suggesting compliant rewrites.
Chicks social media and ad content against Snapchat's advertising and community policies for compliance.
Chicks content against TikTok's advertising and community policies, returning risky phrases and suggested rewrites to avoid flagging or banning.
Chicks video scripts and content against YouTube's community and advertising policies, identifying risky elements and providing rewrites.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@AuditSocials Compliance MCPCheck this before I post: 'Lose 10 pounds in a week with our miracle supplement!'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AuditSocials Compliance MCP — Pre‑Publish Ad & Social Policy Check for AI Agents
A Model Context Protocol (MCP) server that checks AI‑generated social media and ad content against the current advertising and community policies of 8 platforms — Meta (Facebook/Instagram), TikTok, LinkedIn, Google Ads, YouTube, X (Twitter), Snapchat and Pinterest — before it is published. It returns the exact risky phrase, why it's risky, and a compliant rewrite, so posts, ad accounts and campaigns aren't flagged, demonetized, shadow‑limited or banned.
Give your AI writing assistant or agent a pre‑publish compliance guardrail: one self‑describing tool it can call on any draft — no prompt engineering, no SDK.
🛡️ 8 platforms, current policy — advertising + community guidelines for Meta, TikTok, LinkedIn, Google Ads, YouTube, X, Snapchat, Pinterest.
🎯 Actionable findings — the exact risky phrase, the severity, a confidence label, why it violates policy, and a compliant rewrite.
🤖 Built for agents — a single MCP tool with a rich description; your agent discovers and calls it automatically.
⚡ 30‑second setup —
npx, drop in a free key, done. Works with Claude, Cursor, VS Code, Windsurf, Cline and any MCP client.🆓 Free tier — 50 checks / month, no credit card.
Table of contents
Related MCP server: Chinese Sensitive Words MCP Server
Who is this for
AI content & ad‑copy tools that generate social posts, captions, tweets, video scripts or ad creative and need a moderation / brand‑safety pass before publishing.
Agentic workflows & autopilots (Claude, Cursor, custom agents) that draft and schedule content and must not get the account restricted.
Marketing & growth teams and agencies running paid social across many platforms who want to catch policy risk before an ad is rejected or an account is flagged.
Developers building social schedulers, DTC marketing SaaS, influencer tooling, or compliance features who want a policy check as an API/MCP call instead of maintaining 8 platforms' rulebooks themselves.
What it catches
The guardrail combines deterministic pattern rules with AI reasoning over live platform policy. It surfaces risk across categories such as:
Health, wellness & supplements — unrealistic weight‑loss claims, "miracle" / "cure" language, unverifiable "clinically proven" endorsements.
Finance & crypto — "guaranteed returns", "risk‑free", "get rich quick", "zero risk", unsubstantiated return figures.
Misleading & unsubstantiated claims — superlatives, false urgency, implied outcomes you can't back up.
Prohibited & restricted content — categories platforms disallow or gate (regulated goods, sensitive attributes, etc.).
Platform‑specific advertising rules — the things that quietly get ads rejected or distribution reduced rather than outright banned.
Every finding carries a confidence label (firm vs possibly_risky) so your agent can act proportionately — fix the firm ones, review the borderline ones. Findings are grounded in the same live policy engine behind the AuditSocials Policy Tracker; they're never fabricated and are hedged when uncertain.
Quickstart
Get a free API key → https://www.auditsocials.com/compliance-api (50 checks/month, no card).
Add the server to your MCP client (config below) with your key as
AUDITSOCIALS_API_KEY.Ask your agent: "Check this before I post it: …"
{
"mcpServers": {
"auditsocials-compliance": {
"command": "npx",
"args": ["-y", "auditsocials-compliance-mcp"],
"env": { "AUDITSOCIALS_API_KEY": "as_live_..." }
}
}
}Client setup
The server speaks MCP over stdio, so it works with any MCP‑compatible client. Paste the config into your client and drop in your key.
Claude Desktop —
claude_desktop_config.json→mcpServers(config above).Claude Code —
claude mcp addor your.mcp.json→mcpServers.Cursor — Settings → MCP → add the server (same
mcpServersshape).VS Code (GitHub Copilot / MCP) — add to your MCP config with the
command/args/envabove.Windsurf, Cline, Continue, Zed, and other MCP clients — point them at the
npx -y auditsocials-compliance-mcpcommand withAUDITSOCIALS_API_KEYin the environment.
Restart the client after adding the server so it discovers the tool.
Usage — just ask your agent
No prompt engineering. Your agent picks the tool automatically. Examples:
"Check this caption against TikTok and Meta before I post it: '…'"
"Write 3 Instagram captions for my supplement brand — run each through a compliance check first."
"Is this ad copy safe to run on Meta and Google Ads? Rewrite anything risky."
"Review my launch tweet for all 8 platforms and flag policy risks."
The tool
check_social_content_compliance
Checks a piece of social/ad content against the current policies of the 8 platforms and returns an overall verdict plus specific findings.
Param | Type | Notes |
|
| The post / caption / tweet / video script / ad copy to check. Up to 10,000 characters. |
|
| Any of |
|
| Helps apply the right rule set. |
Returns: an overall verdict (e.g. ok / needs_changes), a short summary, and a list of findings — each with severity, confidence, the matched phrase, the reason it's risky, and a suggested compliant rewrite. Each response also reports your remaining monthly credits.
Example response
Input — an ad draft: "Get rich quick! Guaranteed 500% crypto returns, zero risk, invest today."
Verdict: NEEDS_CHANGES
4 potential issue(s) (2 firm) for LinkedIn. Review and apply the suggested fixes before publishing.
• [critical/firm] Guaranteed returns language (Finance & Crypto)
risky text: "Guaranteed"
why: Any language suggesting guaranteed investment outcomes ("guaranteed", "risk-free", "100% returns", …).
fix: Remove any guarantee of financial outcome; state that returns vary and capital is at risk.
• [high/firm] High-risk claim language (Finance & Crypto)
risky text: "Get rich quick"
fix: Rephrase to a hedged, substantiable statement and add any required disclaimer.
… + 2 more
— 49 of 50 credits left this month (free).Pricing & limits
One credit = one full‑quality check (deterministic + AI, all 8 platforms). You're charged on volume, not depth — every tier returns the full result.
Tier | Checks / month | Price |
Free | 50 | $0 — no card |
Starter | 5,000 | $99 / mo |
Growth | 25,000 | $299 / mo |
Scale | custom / OEM |
Check your balance any time at https://www.auditsocials.com/compliance-api/usage or GET /api/v1/credits.
How it works
This package is a thin, open‑source client (~160 lines). All policy data, AI reasoning, quota and metering live server‑side in the hosted AuditSocials Compliance API — the package ships no secrets, no rules, no policy data, and simply forwards your content with your API key over HTTPS. That means the guardrail stays current as platform policies change, without you shipping an update.
your agent ──(MCP/stdio)──▶ auditsocials-compliance-mcp ──(HTTPS + your key)──▶ AuditSocials Compliance API ──▶ live 8‑platform policy engineFAQ
What is the AuditSocials Compliance MCP? An MCP server that gives an AI assistant a single tool to check social media / advertising content against the current policies of 8 major platforms before it's published, returning specific risks and compliant rewrites.
Which platforms are covered? Meta (Facebook & Instagram), TikTok, LinkedIn, Google Ads, YouTube, X (Twitter), Snapchat and Pinterest — advertising and community policies.
Does it guarantee my content will be approved? No. It's a risk‑flagging layer, not a guarantee. Platform review is opaque and changes constantly; the tool surfaces known policy risk and cites the rule behind each flag so you can decide. It deliberately does not claim to predict or guarantee approval.
Do I need an API key?
Yes — a free key (50 checks/month, no card) at https://www.auditsocials.com/compliance-api. Set it as AUDITSOCIALS_API_KEY.
Which MCP clients work? Any MCP client that supports stdio servers — Claude Desktop, Claude Code, Cursor, VS Code, Windsurf, Cline, Continue, Zed and others.
Is my content or key stored? The package sends your content and key over HTTPS to the API to run the check. It ships no secrets itself. See the privacy policy.
How is this different from a generic moderation API? Generic moderation flags toxicity/safety. This checks platform advertising & community policy — the rules that get ads rejected, accounts restricted, or content demonetized — across 8 platforms, with the exact policy reason and a rewrite.
Links
🔑 Get a free API key: https://www.auditsocials.com/compliance-api
📖 API + MCP docs: https://www.auditsocials.com/compliance-api/mcp
📊 Check your usage: https://www.auditsocials.com/compliance-api/usage
📡 Policy Tracker (the live engine behind it): https://www.auditsocials.com/policy-tracker
📦 npm: https://www.npmjs.com/package/auditsocials-compliance-mcp
Keywords: MCP server, Model Context Protocol, AI content compliance, social media policy checker, ad policy compliance API, pre‑publish moderation, brand safety, Meta ad policy, TikTok community guidelines, Google Ads policy, LinkedIn advertising policy, YouTube advertiser‑friendly guidelines, X ads policy, Snapchat ads, Pinterest advertising, compliance guardrail for AI agents.
License
MIT · © AuditSocials
Available Tools
1 toolcheck_social_content_complianceA
Check a piece of social media content (post, caption, tweet, video script, or ad copy) against the CURRENT advertising and community policies of 8 platforms — Meta, TikTok, LinkedIn, Google Ads, YouTube, X, Snapchat, Pinterest — BEFORE it is published. Call this whenever you draft or edit social/ad content so the post, account or ad is not flagged, demonetized, or banned. Returns specific policy risks (with the exact risky phrase, why it's risky, and a compliant rewrite) plus an overall verdict. Use it as a final compliance pass on anything you write for social media.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | The social content to check (post/caption/tweet/video script/ad copy). | |
| platforms | No | Target platforms. Omit to check against all 8. | |
| contentType | No | Type of content (helps apply the right rule set). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full responsibility. It describes output structure in detail (specific policy risks, phrase, reason, rewrite, verdict). However, it does not explicitly state the tool is read-only (no modifications), which is implied but could be clearer. Still, it offers strong behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the purpose, scope, and usage guidance. Every sentence adds value with no redundancy. Well-structured for agent consumption.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 simple parameters with full schema coverage and no output schema, the description fully covers what the tool does, when to use it, what input is expected, and what output to expect. It leaves no significant gaps for a pre-publication compliance check tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description text does not add new semantic value beyond what the schema already provides (e.g., platform list, content type, content). It restates but does not extend.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies a clear verb ('Check'), resource ('social media content'), scope (8 platforms, multiple content types), and purpose (pre-policy compliance). It distinguishes the tool as a final compliance pass, which is unambiguous even without sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'BEFORE it is published', 'whenever you draft or edit', 'as a final compliance pass'. Provides clear context and no ambiguity, even in the absence of sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v0.1.1- First observed
check_social_content_compliance
TDQS
With only one tool, there is no possibility of confusion between tools. The single tool's purpose is clearly defined.
There is only one tool, so no inconsistency exists. The name 'check_social_content_compliance' follows a clear verb_noun pattern and is descriptive.
A single tool for checking social content compliance is reasonable, as the tool is comprehensive in its description. While a few additional tools (e.g., batch checking) might be expected, the count is not inappropriate for a focused utility.
The tool covers the core task of checking text-based content against multiple platforms' policies, including risk identification and compliant rewrites. It lacks support for image/video compliance checks, but for a text-focused checker, it is largely complete.
Maintenance
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