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Microgram: perturbation-layer-classifier

station__algovigilance__microgram-perturbation-layer-classifier native (always callable) algovigilance pv-core Constructa Configa

Classifies pharmacovigilance observations into the 6-layer perturbation pattern model. Given evidence characteristics, identifies which mechanistic layer(s) the observation represents — from molecular binding (L1) through systemic feedback (L6). Exercises μ (Mapping) — each observation maps to its mechanistic origin.

Taxonomy

Linnaean classification joined from the algovigilance taxonomy index via the parent config's rank.

Rank	Value
domain	`Substrata`
kingdom	`Constructa`
phylum	`Configa`
class	`station-config`
order	`algovigilance`
family	`mcp-tool-config`

Characteristics:

substrate: config
domain: pv
lifecycle: continuous
authority: read
compounding: producer
io: agent-request → tool-response

Input schema

is_binding_data boolean — Input variable is_binding_data
is_functional_assay boolean — Input variable is_functional_assay
is_pathway_level boolean — Input variable is_pathway_level
is_cellular_response boolean — Input variable is_cellular_response
is_organ_manifestation boolean — Input variable is_organ_manifestation
is_systemic_feedback boolean — Input variable is_systemic_feedback
evidence_source stringrequired — Input variable evidence_source
has_mechanistic_detail boolean — Input variable has_mechanistic_detail

Example call

POST /api/mcp
Content-Type: application/json

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "station__algovigilance__microgram-perturbation-layer-classifier",
    "arguments": {
      "evidence_source": ""
    }
  }
}

How to invoke from a client

From any MCP-aware client, add https://algovigilance.com/api/mcp as an MCP server, then call this tool by name. From a raw HTTP client, send the JSON-RPC body above to /api/mcp.

Agent-friendly formats

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