Generect Live API MCP Server

Official

by generect

Overview Schema Source Related Servers Discussions(1)Admin

TypeScript

Hybrid

Enrich one company

enrich_company

Read-only

Get a full B2B company profile by providing its Generect ID, LinkedIn URL, domain, or name. Enrich lead records with firmographic data using cached or real-time lookups.

Instructions

Full profile for ONE known company, by Generect id, LinkedIn URL, domain, or name. BILLABLE — about $0.0067 per record found (not-found is refunded) (Tier 0 list price; your account may pay a different rate — call get_balance for your real prices, and read cost.amount_charged in every response for what was actually spent). Not found costs nothing. Domain is the most reliable identifier after id; name matching is fuzzy.

Input Schema

TableJSON Schema

Name	Required	Description
`id`	No	Generect company id.
`mode`	No	Data mode. "database" = cached, sub-second, cheaper, free counts, core filters only. "realtime" = live LinkedIn lookup, 5–60s, pricier, supports every filter. "auto" (default) tries database first and only escalates to realtime if a filter you passed is unsupported there — an escalation is reported in the response. Pick "database" explicitly when a recent cached record is good enough and cost matters more than freshness.
`name`	No	Company name (fuzzy match).
`domain`	No	Company domain without protocol, e.g. "stripe.com".
`compact`	No	Default true: return a small per-company summary (including the Generect `id`, which every later step accepts). Set false for the full raw record (~80 fields) — only worth it when you specifically need skills, education or other deep fields.
`timeout_ms`	No	Request timeout in milliseconds.
`linkedin_url`	No	LinkedIn company page URL.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`cost`	No
`lead`	No
`mode`	No
`found`	No
`company`	No
`test_mode`	No
`test_mode_notice`	No
`vocabulary_warnings`	No
`deprecated_params_ignored`	No

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.9.0Sep 24, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses billability, approximate per-record cost, refund behavior for not-found records, the existence of different account rates, and the pointer to get_balance for real pricing. It also surfaces the database-vs-realtime mode behavior and cost differences via parameter context, adding substantial 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.

Conciseness5/5

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

Two dense, purposeful sentences: the first front-loads the core purpose and inputs, the second packs billing and reliability guidance without filler. Every clause carries decision-relevant information for an agent.

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?

The rich schema, annotations, and output schema cover parameter details and return structure. The description completes the picture with purpose, billing, and identifier reliability. A minor gap is that it never explicitly states that at least one identifier must be provided, though that is strongly implied by the phrasing.

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?

The input schema already has 100% parameter description coverage, so the baseline is 3. The description adds extra semantic value by ranking identifier reliability (domain after id), noting that name matching is fuzzy, and explaining cost implications per lookup. This goes beyond simply restating schema fields.

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 opens with 'Full profile for ONE known company', naming the exact verb, resource, and accepted identifiers (Generect id, LinkedIn URL, domain, or name). This clearly distinguishes it from sibling list/search tools like search_companies or count_companies by emphasizing a single known company rather than discovery or aggregation.

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 gives clear context: this tool is for enriching one already-known company, and it offers identifier reliability guidance ('Domain is the most reliable identifier after id; name matching is fuzzy'). It doesn't explicitly name alternative tools or state when not to use this tool, but the single-record enrichment context is strong enough for selection.

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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