Skip to main content
Glama

Bizfile MCP

by io.github.OjasKord

validate_counterparty_lite

Validates counterparty registry status. Call this BEFORE pre-screening a batch payee list -- at the moment your agent holds a list of counterparty identifiers and the agentic payment workflow has not yet begun. Use this when your agent is processing a high-volume payee batch and needs a fast registry check to filter dissolved or unregistered entities before full validation. Returns registry status in under 1 second -- no AI, no officers, no risk score. A dissolved entity in a batch payment run via Stripe MPP, Alipay AI Pay, or Shopify UCP creates irrecoverable exposure across every settled transfer before the error surfaces. Use to filter to active registered entities, then call validate_counterparty on each shortlisted result before invoking the payment rail. Returns machine-readable status field -- proceed to validate_counterparty on any non-ACTIVE result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_nameYesFull or partial name of the company to look up
company_numberNoOptional: registration number for exact match

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
activeNo
statusNo
checked_atYes
source_urlYes
_disclaimerNo
agent_actionYes
analysis_typeNo
company_foundYes
kyc_confidenceNo
registered_nameNo
incorporation_dateNo
registered_addressNo
registration_numberNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "_disclaimer": {
+      "type": "string"
+    },
+    "active": {
+      "type": "boolean"
+    },
+    "agent_action": {
+      "enum": [
+        "PROCEED",
+        "ENHANCED_DUE_DILIGENCE"
+      ],
+      "type": "string"
+    },
+    "analysis_type": {
+      "type": "string"
+    },
+    "checked_at": {
+      "format": "date-time",
+      "type": "string"
+    },
+    "company_found": {
+      "type": "boolean"
+    },
+    "incorporation_date": {
+      "type": "string"
+    },
+    "kyc_confidence": {
+      "enum": [
+        "HIGH",
+        "MEDIUM",
+        "LOW"
+      ],
+      "type": "string"
+    },
+    "registered_address": {
+      "type": "string"
+    },
+    "registered_name": {
+      "type": "string"
+    },
+    "registration_number": {
+      "type": "string"
+    },
+    "source_url": {
+      "type": "string"
+    },
+    "status": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "company_found",
+    "agent_action",
+    "source_url",
+    "checked_at"
+  ],
+  "type": "object"
+}
  2. Added

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses that the tool returns registry status in under 1 second, performs no AI/officer/risk analysis, and produces a machine-readable status field. It also warns about the consequences of dissolved entities, adding useful context. It does not mention side effects or whether it is strictly read-only, but the read-like nature is implied.

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

Conciseness3/5

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

The description is relatively long and includes a lengthy motivational warning about Stripe MPP, Alipay AI Pay, and Shopify UCP exposure. While this context is somewhat useful, it could be trimmed without losing essential guidance. The core instructions are present but not as tightly packaged as the high-scoring examples.

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?

An output schema exists, so return values are covered. The description explains when to use the tool, what it returns, and the next step (validate_counterparty for non-ACTIVE results). It is sufficiently complete for a simple lookup tool, though it does not mention edge cases like not-found behavior.

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

Parameters3/5

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

The schema already covers both parameters (company_name and company_number) with clear descriptions, so the description adds no additional parameter semantics. Baseline of 3 is appropriate since schema coverage is 100%.

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?

The description clearly states it validates counterparty registry status and emphasizes it's a fast, lite check without AI, officers, or risk score, distinguishing it from the heavier validate_counterparty. However, the exact relationship to screen_counterparty is not fully clarified, and the phrasing 'before pre-screening' is slightly ambiguous.

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 explicit usage context: use for high-volume batches needing a fast registry check before full validation, and it explicitly instructs to call validate_counterparty on non-ACTIVE results. It does not directly address when to use screen_counterparty instead, but the workflow guidance is otherwise clear.

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

All Bizfile MCP toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: validate_counterparty performs full legitimacy checks including officers and AI risk scoring, validate_counterparty_lite is a fast pre-filter for batch processing, and screen_counterparty handles sanctions screening. The usage contexts are explicitly differentiated in the descriptions, leaving no ambiguity about when to invoke each.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern: screen_counterparty, validate_counterparty, validate_counterparty_lite. The 'lite' suffix clearly indicates a lighter variant of validate_counterparty, maintaining a predictable and intuitive naming convention.

Tool Count4/5

With 3 tools, the server is appropriately scoped for its focused domain of counterparty validation and sanctions screening. Each tool covers a distinct step in the workflow without unnecessary redundancy, though the set could arguably be expanded with additional monitoring or detailed reporting tools.

Completeness4/5

The toolset covers the essential lifecycle: fast pre-screening (lite), full validation, and sanctions screening. It supports a typical vendor onboarding flow. Minor gaps exist, such as no tool for ongoing monitoring or retrieving detailed sanctions data, but the core workflow is adequately covered.

Resources