KlearFlow Relay
Server Details
Paid revenue-opportunity intelligence for AI agents. Free discovery; x402 USDC execution on Base.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 2 tools
The two tools both involve revenue leakage and missed calls, making their boundaries somewhat unclear. Inspect operates at business level while recover is item-specific, but an agent might hesitate choosing between them for a particular request.
Both tool names follow a consistent snake_case verb_noun pattern: inspect_revenue_opportunity and recover_revenue. This is predictable and clear across the small set.
With only 2 tools, the server is at the thin end of the typical range. The narrow revenue-recovery purpose partially justifies this, but it still feels minimal for a general agent.
The two tools cover the main workflow: inspecting a business for leakage and recovering specific revenue events. Minor gaps like status tracking or an undo operation exist, but agents can complete the core task without dead ends.
Available Tools
2 toolsinspect_revenue_opportunityInspect Revenue OpportunityBInspect
Inspect a real business for missed-call revenue leakage, estimate recoverable monthly revenue, and return the recommended next commercial action. Execution costs $0.25 by default via x402 Base USDC.
| Name | Required | Description | Default |
|---|---|---|---|
| zipCode | No | ||
| industry | Yes | ||
| businessName | No | ||
| interestLevel | No | ||
| followUpMethod | Yes | ||
| averageJobValue | No | ||
| missedCallsPerWeek | Yes | ||
| estimatedRecoveryRate | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the execution cost of $0.25 via x402 Base USDC, which is a key behavioral trait, and notes that it inspects a 'real business', implying external data access. However, it does not disclose whether the operation is read-only, whether it has side effects, rate limits, or error conditions. While it adds some transparency, it leaves significant gaps for a tool that appears to make a paid external call.
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 two sentences with no filler. It front-loads the core purpose (inspect, estimate, return) and then adds the critical cost detail. Every word earns its place, and it is well-structured for quick scanning.
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?
Despite a clear purpose, the description is incomplete for a tool with 8 parameters and no output schema. It does not explain what the return value looks like (beyond 'recommended next commercial action'), how parameters relate to the computation, or any operational details such as data source requirements or failure modes. The cost mention is useful, but the description leaves too much for the agent to infer about how to correctly call the tool.
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 has 0% description coverage, and the description provides no parameter-level guidance whatsoever. It does not explain the meaning, format, or expected values for any of the 8 parameters, including required ones like industry, missedCallsPerWeek, and followUpMethod. The enums are self-explanatory by their names, but the numeric parameters like averageJobValue and estimatedRecoveryRate have no hints about their significance. The description does not compensate for the schema's lack of descriptions, leaving the agent to guess from parameter names alone.
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's function: inspecting a real business for missed-call revenue leakage, estimating recoverable revenue, and returning a recommended action. It is specific with a verb and resource, and not a tautology of the title. Since there are no sibling tools, there is no need for differentiation, but the description is unambiguous about what it accomplishes.
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 usage whenever one wants to analyze revenue opportunities, but it does not provide explicit guidance on when to use this tool versus alternatives (there are none listed). It also does not mention prerequisites or conditions such as needing specific business data or when not to use it. The purpose is clear enough that an agent would infer usage, but explicit guidance is absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
recover_revenueRecover RevenueAInspect
Turn a missed call, stale lead, unanswered quote, appointment no-show, or failed payment into a prioritized recovery decision packet. No external message is sent; the caller executes the returned action. Execution costs $0.50 by default via x402 Base USDC.
| Name | Required | Description | Default |
|---|---|---|---|
| industry | No | ||
| eventType | Yes | ||
| bookingUrl | No | ||
| paymentUrl | No | ||
| businessName | No | ||
| priorAttempts | No | ||
| preferredChannel | No | ||
| customerFirstName | No | ||
| minutesSinceEvent | Yes | ||
| averageOpportunityValue | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It clearly discloses that no external message is sent, that the caller executes the action, and that execution costs $0.50 by default via x402 Base USDC. This is significant behavioral context beyond the schema. It does not mention failure modes, idempotency, or what happens if payment fails, but the disclosed cost and execution model are strong.
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?
Two sentences, front-loaded with the core transformation and outcome, followed by the critical execution and cost details. Every sentence earns its place; no filler or repetition of schema content.
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 10 parameters, no output schema, and no annotations, the description is fairly complete: it states the purpose, the execution model, and the cost. It lacks guidance on how the parameters influence the decision packet and what the returned action looks like, but the core call context is well covered. The sibling tool is not mentioned, which is a minor gap.
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 0%, so the description must compensate. It does not explain any of the 10 parameters beyond the event types listed in the enum. The description's list of event types mirrors the enum, adding no new meaning. It does not clarify fields like priorAttempts, preferredChannel, or averageOpportunityValue. Baseline 3 is appropriate because the description adds some context (the overall purpose) but leaves parameter semantics to the schema.
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 uses a specific verb ('Turn... into') and names the exact resource (missed call, stale lead, unanswered quote, appointment no-show, failed payment) and the output (prioritized recovery decision packet). It clearly distinguishes itself from the sibling inspect_revenue_opportunity by emphasizing action execution and cost.
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 when to use it: when a revenue-affecting event has occurred and a recovery action is needed. It explicitly states that no external message is sent and the caller executes the returned action, which clarifies a key usage boundary. However, it does not explicitly name the sibling or state when to use inspect_revenue_opportunity instead.
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.
1 tool update
- Added
recover_revenue
1 tool update
- First observed
inspect_revenue_opportunity
Related MCP Connectors
Pay-per-call crypto market intelligence for AI agents. USDC on Base via x402.
Market data and web intelligence for AI agents, paid per call in USDC on Base via x402.
Pay-per-call data tools for AI agents: crypto signal, web reader, SEO audit. x402 USDC on Base.
AI agents find, message & book SMBs; pay per call in USDC on Base via x402. 14 tools, compliant.
Related MCP Servers
AlicenseAqualityCmaintenancePre-trade DeFi intelligence for AI agents. 20 paid x402 endpoints, USDC on Base.2329 npm1MIT- FlicenseAqualityDmaintenancePay-per-call tools for AI agents including trust checks, due diligence, market data, and human-verified approvals, settled in USDC on Base via the x402 protocol.16-
- AlicenseNot gradedqualityCmaintenanceThe open marketplace for the agent economy — Buy any of 24,000+ live x402 services with USDC on Base.6MIT
- AlicenseAqualityAmaintenanceAgent-to-agent marketplace where AI agents discover, invoke, and pay for services from other agents using USDC on Base L2. 72+ services, free tools, x402 micropayments.2039MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.