K-Work Trust
Server Details
Korean business record validation and workflow safety gates for AI agents.
- Status
- Healthy
- Uptime
- 83.8% over 38 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- hycore220/k-work-trust-public-demo
- GitHub Stars
- 0
- Server Listing
- K-Work Trust Public Demo
TDQS
Scored across 3 tools
Each tool performs a single, entirely distinct function: arithmetic, text echoing, and time retrieval. There is no overlap or ambiguity between them.
add and echo are imperative verbs while server_time is a noun phrase, so the naming convention is not fully consistent. However, all names are short, lowercase, and readable.
Three tools is a well-scoped count for a simple utility server, and each tool earns its place by providing a distinct, useful capability.
The tools are unrelated to each other and to the server name, making the intended domain unclear and coverage difficult to assess. Trust-related operations are notably absent if the server name is taken literally.
Available Tools
3 toolsaddAddAInspect
Adds two numbers and returns the sum.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | ||
| b | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full burden of behavioral disclosure. It fully describes the operation (adding two numbers) and the return value (the sum), leaving no room for hidden side effects, state changes, or other behaviors. For a pure arithmetic function, this is complete transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no redundant words. The core operation and return value are front-loaded, and there is no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with two numeric parameters, no annotations, no output schema, and a trivial operation, the description provides all necessary context: what the inputs are, what the tool does, and what the caller receives. Nothing an agent needs to invoke it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only provides names and types (a, b as numbers), with 0% description coverage. The description compensates by clarifying that both parameters are the two addends and that the result is their sum, which gives functional meaning beyond the raw schema. It could only be improved by explicitly naming the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Adds'), the resource ('two numbers'), and the outcome ('returns the sum'). It is not a tautology of the name and clearly distinguishes this tool from the sibling tools echo and server_time.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the clear context: use this tool when you need to add two numbers and get their sum. While it doesn't explicitly exclude siblings, none of them perform arithmetic, so the context is unambiguous and no exclusions are needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
echoEchoAInspect
Echoes the provided text back to the caller.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to echo back |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It clearly conveys the core behavior and result, implying no state change. However, it does not explicitly address formatting, length limits, or edge cases, leaving a minor transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence front-loads the action and result with zero filler. Every word contributes to understanding the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter echo tool with no output schema, the description fully suffices: it tells the agent what the tool does and what it returns. No additional context is necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents the single 'text' parameter with 100% coverage. The description adds no meaning beyond what the schema provides, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Echoes'), a resource ('the provided text'), and a destination ('back to the caller'). Clearly distinguishable from sibling tools add and server_time.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for repeating text back, but it offers no explicit when-to-use guidance, alternatives, or exclusions. For a trivial tool the context is self-evident, but no direct usage guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
server_timeServer timeAInspect
Returns the current server time (ISO 8601, UTC).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It adequately conveys that this is a read-only retrieval operation ('returns') and specifies the output format and timezone (ISO 8601, UTC), which is valuable behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence provides complete information without any filler. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter utility with no output schema, the description is fully sufficient: it states what the tool returns and the exact format of that return value. No additional context is needed for an agent to call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty, so there are no parameter semantics to document. The description appropriately confirms that calling the tool requires no inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: it returns the current server time in ISO 8601 UTC format. This clearly distinguishes it from siblings add and echo, which perform unrelated operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the intended use clear: call this tool whenever the current server time is needed. There are no time-related sibling tools requiring exclusions, so no explicit alternative guidance is necessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
32 tool updates
- Added
add - Removed
authorize_open_world_proof_carrying_autonomy - Removed
compile_agent_plan - Removed
compose_agent_trust_contracts - Added
echo - Removed
estimate_agent_risk_bound - Removed
estimate_agent_tail_risk - Removed
find_agent_counterexample - Removed
issue_agent_trust_certificate - Removed
issue_open_world_trust_certificate - Removed
model_check_agent_temporal_safety - Removed
normalize_korean_address - Removed
normalize_korean_company_name - Removed
normalize_korean_phone_number - Removed
optimize_autonomy_budget - Removed
prove_agent_policy_invariants - Removed
score_agent_evidence_quality - Added
server_time - Removed
validate_agent_action_firewall - Removed
validate_agent_endpoint_fuzzing - Removed
validate_api_contract_drift - Removed
validate_business_registration_number - Removed
validate_document_cross_check - Removed
validate_invoice_readiness - Removed
validate_payment_or_invoice_release - Removed
validate_policy_invariants - Removed
validate_secret_flow - Removed
validate_supply_chain_provenance - Removed
validate_tax_invoice_profile - Removed
validate_technical_due_diligence - Removed
validate_vendor_onboarding - Removed
validate_vendor_reverification
1 tool update
- Added
authorize_open_world_proof_carrying_autonomy
2 tool updates
- Added
compose_agent_trust_contracts - Added
issue_open_world_trust_certificate
3 tool updates
- Added
estimate_agent_tail_risk - Added
model_check_agent_temporal_safety - Added
score_agent_evidence_quality
6 tool updates
- Added
compile_agent_plan - Added
estimate_agent_risk_bound - Added
find_agent_counterexample - Added
issue_agent_trust_certificate - Added
optimize_autonomy_budget - Added
prove_agent_policy_invariants
6 tool updates
- Added
validate_agent_endpoint_fuzzing - Added
validate_api_contract_drift - Added
validate_policy_invariants - Added
validate_secret_flow - Added
validate_supply_chain_provenance - Added
validate_technical_due_diligence
3 tool updates
- Changed
validate_payment_or_invoice_release3 fields changed- added
Input schema / properties / check_companies_houseAdded value: +{ + "default": false, + "description": "When KWT_COMPANIES_HOUSE_API_KEY is configured, request UK Companies House evidence before release.", + "type": "boolean" +} - added
Input schema / properties / check_opensanctionsAdded value: +{ + "default": false, + "description": "When KWT_OPENSANCTIONS_API_KEY is configured, request OpenSanctions screening evidence before release.", + "type": "boolean" +} - added
Input schema / properties / company_numberAdded value: +{ + "description": "UK Companies House company number.", + "type": "string" +}
- Changed
validate_vendor_onboarding3 fields changed- added
Input schema / properties / check_companies_houseAdded value: +{ + "default": false, + "description": "When KWT_COMPANIES_HOUSE_API_KEY is configured, request UK Companies House evidence.", + "type": "boolean" +} - added
Input schema / properties / check_opensanctionsAdded value: +{ + "default": false, + "description": "When KWT_OPENSANCTIONS_API_KEY is configured, request OpenSanctions screening evidence for the company and representative.", + "type": "boolean" +} - added
Input schema / properties / company_numberAdded value: +{ + "description": "UK Companies House company number.", + "type": "string" +}
- Changed
validate_vendor_reverification3 fields changed- added
Input schema / properties / check_companies_houseAdded value: +{ + "default": false, + "description": "When KWT_COMPANIES_HOUSE_API_KEY is configured, request UK Companies House evidence before vendor reuse.", + "type": "boolean" +} - added
Input schema / properties / check_opensanctionsAdded value: +{ + "default": false, + "description": "When KWT_OPENSANCTIONS_API_KEY is configured, request OpenSanctions screening evidence before vendor reuse.", + "type": "boolean" +} - added
Input schema / properties / company_numberAdded value: +{ + "description": "UK Companies House company number.", + "type": "string" +}
2 tool updates
- Changed
validate_payment_or_invoice_release2 fields changed- added
Input schema / properties / check_dart_disclosuresAdded value: +{ + "default": false, + "description": "When KWT_DART_API_KEY is configured, request recent OpenDART disclosure evidence.", + "type": "boolean" +} - added
Input schema / properties / dart_corp_codeAdded value: +{ + "description": "8-digit OpenDART corporation code.", + "type": "string" +}
- Changed
validate_vendor_onboarding2 fields changed- added
Input schema / properties / check_dart_disclosuresAdded value: +{ + "default": false, + "description": "When KWT_DART_API_KEY is configured, request recent OpenDART disclosure evidence.", + "type": "boolean" +} - added
Input schema / properties / dart_corp_codeAdded value: +{ + "description": "8-digit OpenDART corporation code.", + "type": "string" +}
1 tool update
- Added
validate_agent_action_firewall
1 tool update
- Added
validate_vendor_reverification
1 tool update
- Added
validate_document_cross_check
8 tool updates
- First observed
normalize_korean_address - First observed
normalize_korean_company_name - First observed
normalize_korean_phone_number - First observed
validate_business_registration_number - First observed
validate_invoice_readiness - First observed
validate_payment_or_invoice_release - First observed
validate_tax_invoice_profile - First observed
validate_vendor_onboarding
Related MCP Connectors
Korean fact-verification tools for AI agents: business registration, address, DART, apt prices, laws
- mcpweaveOAuthcom.mcpweave
Korea-native MCP gateway: Korean commerce, payments, messaging, gov & finance APIs for AI agents.
Curated Korean AEC expertise for AI agents: KDS·KCS·KS, building law, practice, and the reasoning.
Security gateway for AI agents: policy, approval, and audited execution, no secrets shared.
Related MCP Servers
- FlicenseNot gradedqualityCmaintenanceVerifiable Korea-specific judgment for AI agents — Go/Conditional/Hold verdicts cross-checked by a human expert council, per-report audit endpoint (committee DIDs + signatures). x402/USDC per call ($1–$5), free preview.-
- AlicenseNot gradedqualityBmaintenanceEnables MCP-compatible AI agents to safely act on business backends by enforcing per-agent permissions, autonomy thresholds, human approval with review-and-edit, and full audit trails.MIT
- AlicenseAqualityAmaintenanceAuditable records of human decisions over AI agent work. Approvals, edits, overrides, escalations.6639103Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to search and retrieve Korean laws, regulations, administrative rules, legal interpretations, and precedents via official APIs for legal review workflows.1MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.