Versium REACH

Demographic Append Mcp Tool

demographic_append

Read-onlyIdempotent

Append consumer marketing records with household and lifestyle insights for audience segmentation, across demographic and lifestyle categories

**Tips for Best Results:**
- Request only the insight categories you need to keep responses focused
- Combine name, location, and digital identifiers (email or phone) for higher match confidence
- Use `cfg_required` or `rcfg_require_value` to enforce must-have attributes in the response

Input Schema

Name	Required	Description	Default
`zip`	No	5 digit ZIP code
`city`	No	City name
`last`	No	Person's last name
`email`	No	Email address to enrich
`first`	No	Person's first name
`phone`	No	10 digit phone number without formatting
`state`	No	Two-character state code (US)
`address`	No	Street address (line 1)
`outputs`	Yes	Insight categories to return. Choose at least one category
`address_2`	No	Apartment or unit number
`match_type`	No	Match at household (hhld) or individual (indiv) level	hhld
`cfg_maxrecs`	No	Maximum number of records to return
`cfg_required`	No	Comma or semi-colon separated response fields that must be populated for a record to be returned
`rcfg_require_value`	No	Field/value requirements in "Field=Value" format. Example: ["Language=Spanish"]

Output Schema

Name	Required	Description
`results`	No	Records returned by the Operations API. Record fields pass through unchanged.
`query_id`	No
`warnings`	No
`input_query`	No
`num_matches`	No	Number of matching queries.
`num_results`	No	Number of records returned.
`match_counts`	No	Sparse match counts. An absent key means zero.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 29, 2026

changedInput schema / properties / outputs / items / enum

Previous value: -[
-  "demographic",
-  "financial",
-  "lifestyle",
-  "political",
-  "full_demographic"
-]New value: +[
+  "demographic",
+  "lifestyle"
+]

Changed1 schema field changedAug 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "input_query": {
+      "type": [
+        "object",
+        "null"
+      ]
+    },
+    "match_counts": {
+      "description": "Sparse match counts. An absent key means zero.",
+      "type": [
+        "object",
+        "null"
+      ]
+    },
+    "num_matches": {
+      "description": "Number of matching queries.",
+      "type": [
+        "integer",
+        "null"
+      ]
+    },
+    "num_results": {
+      "description": "Number of records returned.",
+      "type": [
+        "integer",
+        "null"
+      ]
+    },
+    "query_id": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "results": {
+      "description": "Records returned by the Operations API. Record fields pass through unchanged.",
+      "items": {
+        "type": "object"
+      },
+      "type": [
+        "array",
+        "null"
+      ]
+    },
+    "warnings": {
+      "items": {
+        "type": [
+          "string",
+          "integer",
+          "number",
+          "boolean",
+          "object",
+          "array",
+          "null"
+        ]
+      },
+      "type": [
+        "array",
+        "null"
+      ]
+    }
+  },
+  "type": "object"
+}

First observedAug 19, 2026

TDQS

A3.8/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely non-structured behavior: that match confidence rises with more identifiers, and that cfg_required/rcfg_require_value can suppress records, which affects what the agent gets back. It does not say what happens on a no-match record.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in the first sentence, with configuration tips scoped under a clear heading. Content is well sized for a 14-parameter tool; only minor overhead from leading whitespace and the redundant title restatement.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the description needn't document return values, and annotations cover safety. It covers purpose, matching strategy, and result filtering adequately; the notable remaining gap is behavior on unmatched records and any cost/credit implications of an enrichment call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The tips go beyond field definitions by advising which parameters to combine for higher match confidence and by explaining the practical role of cfg_required and rcfg_require_value as response filters, adding strategy the schema does not convey.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Append consumer marketing records') plus the data domain (household and lifestyle insights) and the intended use case (audience segmentation). This implicitly differentiates it from b2b or firmographic append siblings, but never names them explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The tips give input-strategy guidance (request only needed categories, combine identifiers, enforce required fields), which tells the agent how to call it well. However, there is no explicit statement of when to prefer this tool over contact_append, b2c_listgen_*, or the B2B append siblings, so tool selection is left to inference from the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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