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AnomalyArmor

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Monitor data quality, detect schema drift, and manage alerts via MCP.

MCP ServerOtherLocal (stdio) 1
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Updated 2026-06-15

What is the AnomalyArmor MCP server?

AnomalyArmor delivers AI-powered data observability directly inside MCP-compatible tools. Users can query health summaries, configure monitoring rules, investigate alerts, and explore lineage without leaving their AI client.

The server uses a consolidated tool design where each domain tool accepts an action parameter to reduce context usage while supporting full functionality for assets, metrics, and schema monitoring.

Install & connect

Add this to your MCP client config. Pick your client below and copy.

{
  "mcpServers": {
    "armor-mcp": {
      "url": "https://mcp.anomalyarmor.ai/mcp"
    }
  }
}

Package: armor-mcp (pypi)

Tools it exposes

15 tools your AI client can call once connected.

health_summary— Overall data health across all assets
get_todays_briefing— Daily AI briefing with alerts, freshness, and coverage gaps
get_alerts_summary— Alert counts by severity and status
list_alerts— Query alerts with filters
statusseverityasset_idfrom_dateto_date
list_inbox_alerts— Unresolved alerts inbox
statuslimit
update_alert— Acknowledge, resolve, snooze, or comment on alerts
alert_idaction
get_alert_trends— Alert trends over time
period
list_alert_rules— List configured rules
asset_idis_active
create_alert_rule— Create new alert rule
asset_idrule_type
manage_alert_rule— Update, delete, enable/disable, or duplicate rules
rule_idaction
list_assets— List monitored assets
sourceasset_typesearch
create_asset— Create data source
namesource_typeconnection_config
manage_asset— Update, delete, test connection, or trigger discovery
asset_idaction
get_freshness_summary— Freshness overview across all assets
check_freshness— Check specific table freshness
asset_idtable_path

Example prompts

Once connected, try asking your AI client:

“Show me today's data health briefing
“List unresolved alerts from the last 24 hours
“Check freshness for the orders table in my Snowflake source
“Create a schema baseline for the finance database

Configuration

Environment variables this server needs.

VariableRequiredDescription
ARMOR_API_KEYsecretYesAnomalyArmor API key (aa_live_*). Generate at https://app.anomalyarmor.ai/settings/api-keys.

Security & permissions

Requires ARMOR_API_KEY environment variable for API access; runs locally via stdio and connects to your AnomalyArmor account to read and manage data assets and alerts.

What you can do with AnomalyArmor

Daily data health checks

Run health_summary or get_todays_briefing to get an overview of asset freshness, alerts, and coverage gaps.

Alert investigation and resolution

Use list_alerts and update_alert to filter, review, and resolve data quality issues from within the chat.

Schema and freshness monitoring setup

Create monitoring schedules and baselines for tables using create_asset, setup_freshness, and enable_schema_monitoring.

How to use AnomalyArmor

  1. 1Sign up at anomalyarmor.ai and generate an API key.
  2. 2Install via uvx armor-mcp or the Claude Code plugin.
  3. 3Set the ARMOR_API_KEY environment variable.
  4. 4Add the server to your MCP client configuration using stdio transport.
  5. 5Start chatting with prompts about data health, alerts, or monitoring.

AnomalyArmor: pros & cons

Pros

  • +52 consolidated tools reduce context window usage
  • +Covers alerts, schema drift, freshness, lineage, and quality metrics
  • +Works seamlessly with Claude Code, Cursor, and other MCP clients
  • +Includes both function tools and slash-command skills

Cons

  • –Requires paid AnomalyArmor account and API key
  • –Tool list is long and may need careful prompt engineering
  • –Primarily focused on data observability rather than general tasks
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Frequently asked questions

ARMOR_API_KEY must be set to authenticate with the AnomalyArmor API.

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