SentEdge Idea Machine
Server Details
Buy adversarially-debated AI product ideas over x402: $0.10 pulls, $1 buyouts, USDC on Base.
- Status
- Healthy
- Uptime
- 99.9% over 41 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 7 tools
Each tool has a clearly distinct purpose: listing, teasers, samples, paid full access, exclusive buyout, pricing economics, and payment instructions. The only mild ambiguity is between get_full_idea and buy_exclusive, but their descriptions clearly separate non-exclusive from exclusive access.
Most tools follow a consistent get_/list_/buy_ verb pattern, and snake_case is used throughout. The exceptions are 'economics' and 'how_to_pay', which are descriptive nouns/phrases rather than verb_noun names, creating minor inconsistency.
Seven tools is well-scoped for a focused marketplace/payment server. Each tool covers a necessary step in the buyer journey without redundancy or bloat.
The tool surface covers the full lifecycle: discover (list_ideas), evaluate (teaser, sample, economics), pay (how_to_pay), and acquire (get_full_idea, buy_exclusive). No obvious missing operation prevents a user from completing the intended workflow.
Available Tools
7 toolsbuy_exclusiveExclusive buyout ($1.00 USDC)AInspect
Buy an idea outright for $1.00 USDC via x402: full markdown delivered, idea delisted from sentedge.ai, no further sales. First come, first served — a losing racer is never charged. This tool returns the exact payment instructions.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Idea slug |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description provides key behavioral traits: the exclusive buyout effect (delisting), the race condition ('first come, first served' and losing racer not charged), and the return type (payment instructions). It could be more explicit about failure modes or authorization needs, but it discloses the main behavioral implications.
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 three sentences with no redundancy: first sentence states core action, second adds concurrency detail, third clarifies return type. Every sentence adds value, and the most critical information is front-loaded.
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?
Given the tool's simplicity (1 parameter, no output schema), the description covers all essential aspects: what it does, how to use it (slug), key behavioral notes (race, delisting, no charge on loss), and what to expect (payment instructions). Minor omissions like exact payment flow are reasonable for this scope.
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 single parameter 'slug' is described in the schema as 'Idea slug', which is self-explanatory given the context. Schema coverage is 100%, so the description adds no additional meaning beyond what the schema provides. Baseline 3 is appropriate.
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 action ('Buy an idea outright'), the resource ('idea'), the price ($1.00 USDC), the method (via x402), and the effects (full markdown delivered, idea delisted). It distinguishes from siblings like get_full_idea (read-only) and how_to_pay (payment info).
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 the tool (to purchase exclusivity) and notes the 'first come, first served' race condition. However, it lacks explicit guidance on when not to use it or direct comparison with alternatives like get_full_idea for non-exclusive access.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
economicsMarketplace economics (free)AInspect
Free: what this catalogue costs to acquire in full, and the break-even probability a purchase has to clear (p ≥ price / value). Every figure is computed from the live catalogue at call time and is reproducible from the free endpoints. Claims no return — it gives you the threshold and lets you supply the prior. Call this before deciding whether to spend.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden. It discloses that figures are computed live from the catalogue and reproducible, and notes 'Claims no return' — meaning it offers only a threshold, not a recommendation. This gives useful behavioral context beyond a simple read-only calculation.
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 sentences, each adding essential information: headline 'Free:', what it computes, and when to call it. The phrase 'Claims no return' is slightly ambiguous but still concise. Overall compact and front-loaded with the most important detail.
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 having no output schema, the description explains the conceptual output ('threshold') but not the exact return structure or data format. As a simple zero-parameter tool, the essential context is covered, but clarity about what the response contains would improve completeness.
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, so the baseline of 4 applies. The description doesn't need to explain parameters since there are none, and the schema is already fully covered.
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 provides the acquisition cost and break-even probability threshold, using specific language like 'cost to acquire in full' and 'break-even probability.' It is distinct from sibling tools like buy_exclusive or how_to_pay, which focus on purchasing/payment rather than economic analysis.
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?
Explicitly says 'Call this before deciding whether to spend,' providing a clear situational trigger. However, it does not explicitly name alternatives or mention when not to use it, though the context is strong enough to differentiate it from siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_full_ideaPull full idea ($0.003 USDC)AInspect
Get the complete idea markdown — non-exclusive, the idea stays listed. Costs $0.003 USDC via x402. This tool returns the exact payment instructions; settle with an x402 client against the HTTP endpoint.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Idea slug |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the non-destructive nature ('non-exclusive, the idea stays listed') and the payment requirement. However, it does not specify behavior on payment failure or rate limits, which is reasonable for a simple read tool.
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, no fluff. First sentence states purpose, second covers payment and instructions. Very concise and front-loaded.
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 description explains the payment flow but does not specify the output format or the two-step process (returns payment instructions, not idea directly). An output schema is absent, so the description could be more complete regarding the return value.
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%, with the only parameter 'slug' described as 'Idea slug'. The description adds no additional detail about the parameter, meeting the baseline of 3.
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 verb 'Get' and resource 'complete idea markdown', and specifies it is non-exclusive, distinguishing it from siblings like 'buy_exclusive' and 'get_idea_teaser'.
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 provides clear context on when to use the tool (to get the full idea) and includes payment instructions. It does not explicitly list when not to use it, but the sibling names imply alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_sample_full_ideaFree sample (full markdown)AInspect
Free: one complete idea delivered exactly as a paid pull or buyout delivers it — the full unstripped council note with debate log, pain evidence, data strategy, success criteria, and process flow. Inspect the goods before spending a cent.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description fully explains behavior: returns a complete, unstripped idea identical to paid versions. Lists all included sections (debate log, pain evidence, etc.) and states it's free. No side effects or permissions noted, but adequate for a read-only sampling tool.
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, zero wasted words. First sentence enumerates deliverable content; second sentence states purpose ('Inspect the goods'). Front-loaded with key purpose: free full sample.
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?
Given no parameters and no output schema, description fully informs the agent: returns a complete free idea with specific sections, identical to paid version. No gaps for this simple 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?
Input schema has zero parameters, so schema coverage is 100%. Description adds no parameter info (unnecessary) but compensates by detailing what the tool returns, adding value beyond the empty 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?
Name and title clearly indicate a free sample of a full idea. Description specifies it delivers a complete idea with detailed sections (council note, debate log, etc.), distinguishing it from siblings like get_idea_teaser and get_full_idea.
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?
Explicitly states 'Free' and 'Inspect the goods before spending a cent,' implying use for previewing full ideas without payment. Context from sibling names clarifies when to use this vs teaser or paid versions, but lacks explicit when-not-to-use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
how_to_payHow to pay (x402 guide)AInspect
Free: the complete guide to buying Idea Machine ideas — pricing, x402 flow, endpoints, and recommended clients.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It calls itself 'the complete guide', which implies a read-only, non-destructive behavior. While not explicitly stating side effects, the informational nature is evident.
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?
One sentence that is front-loaded with 'Free: the complete guide' and efficiently covers all key aspects with no superfluous words.
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 no parameters and no output schema, the description fully captures its purpose and contents. No additional context is needed.
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?
With zero parameters, the description adds value by summarizing the content of the guide (pricing, flow, endpoints, clients), which is beyond the empty 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 clearly states the tool is a guide for buying Idea Machine ideas, covering pricing, x402 flow, endpoints, and clients. This distinguishes it from sibling tools that perform actions like buying or retrieving ideas.
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 explicit guidance on when to use this tool versus alternatives. The description implies it is informational, but does not provide context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_ideasList ideasAInspect
List all Idea Machine ideas (free). Each entry includes status (available|sold), prices, and the x402 endpoints for the paid actions.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max ideas to return, newest first (default 50) | |
| status | No | Filter by sale status (default: all) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must convey behavioral traits. It states the tool lists ideas and includes specific output fields (status, prices, x402 endpoints). However, it does not disclose whether the operation is read-only, pagination behavior (despite having a 'limit' parameter), or any side effects. The description is adequate but not thorough for a tool without annotations.
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 consists of two concise sentences with no redundancy. The first sentence states the action and purpose, the second lists included data. Every word adds value, and the structure is front-loaded with the most critical 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?
Given the simple parameter set (2 optional params), no output schema, and no annotations, the description covers the tool's functionality well: it specifies what the tool returns and its scope. A minor gap is the lack of mention of pagination or that 'limit' controls page size (though implied), but overall it's sufficiently complete 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 input schema covers both parameters ('limit' and 'status') with 100% description coverage, so the description adds no additional meaning. It mentions output fields but not parameter behavior or defaults. Baseline score of 3 is appropriate since the schema already documents both parameters sufficiently.
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 'List' and resource 'all Idea Machine ideas', immediately clarifying the tool's function. It explicitly distinguishes from sibling tools (e.g., buy_exclusive, get_full_idea) by stating it returns a list of ideas with status, prices, and x402 endpoints, leaving no ambiguity about its purpose.
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 for browsing available/sold ideas but does not provide explicit when-to-use or when-not-to-use guidance. While the context of siblings suggests alternatives, the description itself lacks direct exclusions or comparisons, leaving the agent to infer appropriate scenarios from the tool name and sibling list.
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
economics
6 tool updates
- First observed
buy_exclusive - First observed
get_full_idea - First observed
get_idea_teaser - First observed
get_sample_full_idea - First observed
how_to_pay - First observed
list_ideas
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