Versium REACH

Contact Append Mcp Tool

contact_append

Read-onlyIdempotent

Enrich consumer records with contact information including emails, phone numbers, and mailing addresses

**Tips for Best Results:**
- Provide as many input fields as possible to improve match quality
- Use `indiv` match type when targeting a specific person
- Request one output type per call when optimizing for match quality (especially for phone outputs)
- Set `cfg_maxrecs` when more than one record is acceptable

Input Schema

TableJSON 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	Types of contact data to return. Choose at least one output type
`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
`rcfg_max_emails`	No	Maximum number of emails per record (use with email_multiple)
`rcfg_exclude_domains`	No	Domains to exclude from alternate email results

Output Schema

TableJSON 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.

TDQS

A4.2/5.0

Behavior3/5

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

Annotations already cover readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description need not repeat those. The description adds context about match quality and output types, but does not disclose additional behavioral aspects (e.g., rate limits, error handling). No contradiction with annotations.

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

Conciseness5/5

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

A single concise opening sentence followed by four actionable bullet points. Every sentence provides genuine guidance; there is no filler or redundancy.

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 14 parameters, full schema coverage, and an output schema present, the description covers the essential usage considerations and best practices. It does not explain every parameter but the schema does; the description adds critical guidance on match types and output optimization.

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 coverage is 100%, so parameters are documented. The description adds value with tips linking specific parameters to outcomes (e.g., 'use indiv match type when targeting a specific person', 'Request one output type per call when optimizing for match quality'), enhancing understanding beyond the schema.

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

Purpose5/5

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

The description states 'Enrich consumer records with contact information including emails, phone numbers, and mailing addresses', which is a specific verb+resource+scope. It distinguishes from sibling tools like firmographic_append (company data) and demographic_append (demographics) by explicitly targeting consumer records and contact information types.

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

Usage Guidelines4/5

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

The description provides practical tips (e.g., 'Provide as many input fields as possible', 'Use indiv match type when targeting a specific person') that guide usage. It implies when to use this tool (consumer enrichment) but does not explicitly mention alternative tools or when not to use it, falling short of complete exclusion guidance.

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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TDQS

A4.1/5.0

Disambiguation5/5

Each tool targets a distinct resource and action: list generation (B2B vs B2C), enrichment (contact, demographic, firmographic, C2B, IP-to-domain), project/list management, job lifecycle, and validation. No two tools appear to do the same thing, so an agent can reliably select the correct one.

Naming Consistency5/5

All tool names follow the verb_noun pattern consistently, using verbs like list, show, create, preview, search, validate, append, and estimate. Even the segmented append tools (c2b_append, contact_append, demographic_append, firmographic_append, ip_to_domain_append) follow the same pattern with clear noun modifiers. No mixed conventions or vague verbs.

Tool Count4/5

With 19 tools, this is on the higher side but still well-scoped for a data enrichment and list-building platform. The count covers distinct functional areas (audience estimation, enrichment, job/project management, list inspection, documentation) without unnecessary bloat. It feels slightly heavy but each tool earns its place.

Completeness4/5

The tool surface covers the core workflows: estimating audiences, creating and monitoring jobs, managing projects and lists, and enriching records with various data types. Minor gaps exist, such as no explicit delete/update operations for projects or lists, and no direct file download for list contents (though preview_list and show_list provide partial coverage). These are non-blocking gaps that agents can work around.

Resources

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