Booking Request
Server Details
Self-authenticating booking-request receipt anchored to the Knox chain; never represents a person.
- Status
- Healthy
- Uptime
- 99.7% over 40 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-03-26
- URL
TDQS
Scored across 3 tools
Each tool addresses a separate step in the workflow: enumerating agents, creating a booking request, and verifying an existing booking. There is no overlap or ambiguity between the three operations.
All tool names follow a consistent verb_noun pattern: list_represented_agents, request_booking, verify_booking. The style is uniform and predictable.
With three tools, the server provides a focused but complete minimal workflow. The count is on the lower end but well-scoped for a booking-request primitive; not thin enough to feel incomplete.
The core lifecycle is covered: discover agents, create a booking request, and verify it. Missing operations like update or cancel are not essential given the stated primitive nature and the explicit exclusion of payment/acceptance handling.
Available Tools
3 toolslist_represented_agentsAInspect
Enumerate the Bonis Concierge represented-agent roster. Returns slug, name, charter, bureau, archetype, liveness ('live' = verifiable POST endpoint and Knox event-chain integration today / 'charter' = description filed, integration in progress), and capability-page URL for each agent.
| Name | Required | Description | Default |
|---|---|---|---|
| livenessFilter | No | Optional filter on liveness. Default: 'all'. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It does not disclose any behavioral details such as data volume, authentication needs, or rate limits. The read-only nature is implied but not explicitly stated.
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 sentence that efficiently conveys the tool's purpose and output. Every part is necessary, and there is no superfluous information.
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?
The tool has only one optional parameter and no output schema. The description covers the return fields and filter semantics adequately. It doesn't address pagination or limits, but the tool is likely returning a small roster, so it's acceptable for a list operation.
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 schema already provides a description for the single parameter (livenessFilter), achieving 100% coverage. The tool description adds value by explaining the meaning of the enum values ('live' and 'charter') in the context of agent status, which helps the agent select the appropriate filter.
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 clearly states the tool is used to 'Enumerate the Bonis Concierge represented-agent roster' with a specific verb and resource. It lists the exact fields returned (slug, name, charter, etc.), and the sibling tools are action-oriented (booking), so this read-only listing tool is well-differentiated.
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?
No guidance on when to use this tool versus alternatives. There is no mention of use cases, when not to use it, or any prerequisites. The description simply explains what it returns.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
request_bookingAInspect
Anchor a booking request for a represented Bonis Concierge agent. Returns a booking bundle: Knox anchor record + C2PA-aligned envelope (subset of C2PA 1.4 — adapted for booking events) + FRE 902(13)/(14)-shape representation affidavit. The agency does not adjudicate the merits of any booking, does not guarantee acceptance by the listed agent, does not handle payment under this primitive, and does not represent any natural person. Requires a Knox Bearer API key on the Authorization header — unauthenticated calls are rejected.
| Name | Required | Description | Default |
|---|---|---|---|
| brief | Yes | Plain-language description of the booking (10–4000 chars). | |
| notes | No | Optional free-form notes (≤ 2000 chars). | |
| startBy | No | Optional ISO-8601 date or date-time when the booking should begin. | |
| agentSlug | Yes | Roster slug of the listed agent (e.g., 'ofac-sdn-screening', 'content-provenance'). Must match the published Bonis Concierge roster — call list_represented_agents to enumerate. | |
| archetype | No | Optional requested presentation archetype if the listed agent supports multiple. | |
| budgetUsdMax | No | Optional maximum USD budget signal. Discovery field — no payment is collected under this primitive. | |
| contactEmail | No | Optional contact email (hashed before anchoring). Provide at least one of contactEmail or contactKnoxKeyId. | |
| contactKnoxKeyId | No | Optional Knox API key ID. Provide at least one of contactEmail or contactKnoxKeyId. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the authentication requirement (Knox Bearer API key, unauthenticated rejected), the exact return bundle (three components), and disclaimers about adjudication, acceptance, payment, and representation. This goes well beyond the schema and paints a complete behavioral picture.
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 dense paragraph, but every sentence earns its place: purpose, return contents, disclaimers, and auth. It is front-loaded with the purpose. It could be improved with bullet points or line breaks, but overall it is efficient and appropriately sized for the complexity.
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 an 8-parameter tool with no annotations and no output schema, the description covers the essential operational context: return shape, auth requirements, and critical disclaimers. It does not explain the C2PA envelope in depth, but that is abstract and the schema covers parameters. The lack of an explicit usage disclaimer against siblings is a minor gap, but the description is largely complete.
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?
Schema description coverage is 100%, so the schema already documents all 8 parameters. The description adds no parameter-specific detail beyond what appears in the schema (e.g., hashing of contactEmail is already in the schema). Thus, baseline 3 is appropriate–the description does not need to compensate.
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 the specific action ('Anchor a booking request') with a clear resource (represented Bonis Concierge agent) and immediately lists what the tool returns. It implicitly distinguishes itself from siblings (list_represented_agents and verify_booking) by focusing on creating an anchored request, not listing or verifying.
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 usage is implied: use this to anchor a booking request. However, the description never explicitly mentions when to use it versus the sibling tools, nor does it provide exclusionary guidance. The agent has to infer the distinction from the purpose, so it's adequate but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_bookingAInspect
Verify an anchored booking-request record. Given a SHA-256 anchor hash (the payload_hash from a prior request_booking call), return the anchor record, predecessor hash, sequence number, and timestamp. Public — no authentication required. The verification path is also accessible at GET /api/knox/verify?hash=.
| Name | Required | Description | Default |
|---|---|---|---|
| hash | Yes | SHA-256 anchor hash (64 lowercase hex chars). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes public, read-only nature and returned fields. No annotations present; description provides minimal behavioral context but lacks details on limits or error conditions.
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?
Three concise sentences: purpose, usage, and public access. Front-loaded with core action. No fluff.
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?
Simple tool with single parameter; description covers input source, returned fields, public nature, and REST endpoint. Adequate for tool selection and invocation.
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?
Schema coverage 100%; description adds context by specifying hash is from prior request_booking call and confirms hex format. Exceeds schema-only understanding.
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 verb 'verify' and resource 'anchored booking-request record'. Lists returned fields and input hash source. Differentiates from sibling 'request_booking' and 'list_represented_agents'.
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?
Mentions public access (no auth needed) and REST endpoint alternative. Does not explicitly state when to use versus siblings, though implication is clear.
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.
3 tool updates
- First observed
list_represented_agents - First observed
request_booking - First observed
verify_booking
Related MCP Connectors
Post-quantum, tamper-evident receipts for agent actions. Ed25519 + ML-DSA-65, offline verify.
Privacy-first document verification anchored to the public ledger.
Issue & verify signed (ed25519), hash-chained, timestamped provenance receipts for agent actions.
Read-only gateway for durable agent identity, consent, recognized work, and signed receipts.
Related MCP Servers
- AlicenseAqualityBmaintenanceEnables AI agents to create cryptographically verifiable receipts of their delegated work, with capabilities for multi-party approval and offline verification.1147 npmApache 2.0
- FlicenseNot gradedqualityCmaintenanceCryptographically anchored, tamper-evident evidence receipts for AI agents — verified run receipts, existence-at-time proofs, and cited answers from an anchored public record. Remote MCP with proof-gated settlement; attests existence and integrity, never truth.-

EVIDIQ Notary MCPofficial
AlicenseNot gradedqualityBmaintenanceCryptographic receipt layer for AI inferences. Enables notarization and verification of AI outputs with on-chain proofs via x402 payment.1MIT
evermint-mcpofficial
AlicenseNot gradedqualityCmaintenanceTamper-evident receipts for AI agent actions. The notary layer for agent-to-agent transactions.23 npm1MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.