MCP 서버는 BTCMatic agent API를 위한 것입니다: 자율 에이전트를 위한 호출당 지불 비트코인 컨텍스트 — 자체 보관 보안 레이더, 수수료 백분위, 가격 변동 창 및 조건 빈도 — 라이트닝을 통해 sats로 지불. 계정, API 키, 신용카드 없음: API는 인보이스와 함께 402로 응답하고, 에이전트의 지갑이 지불하며, 도구 호출은 preimage로 완료됩니다.
BTCMatic은 비트코인 이벤트 엔진입니다; 이 패키지는 에이전트의 진입점입니다. 여기의 모든 것은 읽기 전용 컨텍스트입니다 — 규칙을 생성하거나, 주문을 하거나, 누구에게 알리거나, 자금을 건드릴 수 없습니다.
도구 | 유료 | 설명 |
| 아니요 | 가격, 선불 한도 및 결제 흐름 — 먼저 호출하세요 |
| 예 | 공개/확인된 자체 보관 사고, 제품별 대화 수와 고유 소스 수, 소스별 정확도 원장 |
| 예 | 1시간/24시간/7일 변동이 포함된 최신 가격, 다음 블록 수수료 + 90일 백분위, 멤풀 크기; 오래된 값은 제외하고 공백은 보고됨 |
| 예 | 지난 90일 동안 |
| 아니요 | 선불 충전 인보이스 발행 |
| 아니요 | preimage로 충전을 증명 → 베어러 토큰 (한 번만 표시) |
| 아니요 | 선불 잔액 및 남은 호출 수 |
유료 호출 한 번은 약 21 sats입니다 (실시간 가격은 btcmatic_discover에 있습니다).
Related MCP server: x402-api
증명 없이 유료 도구를 호출하세요. 결과는 오류가 아닌 데이터로서의 402 제안입니다: { kind: "offer", price_sats, bolt11, payment_hash, next_step }.
지갑이 bolt11을 지불하고 preimage를 표시합니다.
동일한 도구를 { payment_hash, preimage }와 함께 다시 호출하세요. 증명은 일회용입니다.
선불: btcmatic_topup → 지불 → btcmatic_topup_claim → 토큰. 서버를 BTCMATIC_AGENT_TOKEN=agt_…로 시작하면 모든 유료 도구가 잔액에서 차감됩니다; 잔액이 0이면 도구는 { kind: "topup_needed" }로 응답합니다.
이 서버는 키를 보관하지 않으며 지불하지 않습니다. 증명을 이동할 뿐입니다; 지불은 항상 당신이 제어하는 지갑의 결정입니다. 증명 형식은 Authorization: L402 <payment_hash>:<preimage>입니다 — 결제 해시는 BTCMatic이 발행한 인보이스를 지칭하고 sha256(preimage) = payment_hash가 증명이므로 macaroon이 필요 없습니다.
{
"mcpServers": {
"btcmatic": {
"command": "npx",
"args": ["-y", "btcmatic-mcp-server"],
"env": { "BTCMATIC_AGENT_TOKEN": "agt_…" }
}
}
}BTCMATIC_AGENT_TOKEN은 선택 사항입니다 (없으면 호출당 402 흐름). BTCMATIC_API_URL은 API 기본 URL을 재정의합니다 (기본값 https://api.btcmatic.com).
소스별 정확도는 BTCMatic이 수동으로 설정하고 btcmatic.com/radar에 게시하는 라벨에서 비롯됩니다; 라벨이 없는 소스는 정확도를 전혀 표시하지 않습니다.
수수료 백분위, 변동 창 및 빈도는 공개 시리즈에 대한 기술 통계입니다. 과거를 설명할 뿐이며, 어떤 것도 예측하지 않으며 여기의 어떤 것도 매수 또는 매도 추천이 아닙니다.
모든 유료 응답에는 지불된 가격, 남은 잔액, 면책 조항 및 가입 링크가 포함된 meta 블록이 포함됩니다 — 동일한 데이터는 BTCMatic 계정으로 무료입니다; 이 API는 계정을 가질 수 없는 클라이언트를 위해 존재합니다.
pnpm install
pnpm build && pnpm test && pnpm lint
BTCMATIC_API_URL=http://localhost:3000 node dist/cli.js # stdio transport에이전트 API 문서: https://btcmatic.com/integrations/agents
OpenAPI (agent 태그): https://api.btcmatic.com/docs
자동화를 위한 BTCMatic (API 키, n8n): https://btcmatic.com/integrations/n8n
MIT
Counts, at hourly resolution, how often a single condition became true in the trailing 90 days (rising edges — what a throttled rule would have fired) and how many hours it held. Metrics: price_change_pct (needs window 1h|24h|7d), fee_next_block (sat/vB), mempool_vsize (vbytes). Operators: <, <=, >, >=. Past frequency, not a forecast.
| Name | Required | Description | Default |
|---|---|---|---|
| op | Yes | ||
| value | Yes | ||
| metric | Yes | ||
| window | No | price_change_pct only; default 24h | |
| preimage | No | The preimage your wallet showed after paying the bolt11 from the offer | |
| payment_hash | No | From a previous 402 offer (with preimage) — proof of a settled per-call payment |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. It reveals that it counts rising edges (throttled rule fires) and hours held, and clarifies it is not a forecast. However, it omits details like credit consumption (though title says paid), exact output format (e.g., integer counts), or any side effects. The 'rising edges' context adds value, but completeness is limited.
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 action, and efficient. Every sentence adds unique information: the first explains the counting mechanism and metrics/operators; the second clarifies scope ('Past frequency'). No fluff or redundancy.
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 complexity (6 params, no output schema), the description adequately explains the tool's purpose, granularity, and output (counts and hours held). It also flags the 'not a forecast' caveat. It does not spell out the exact response structure or payment preimage requirements, but those are partially covered by schema descriptions and the 'paid' title. Overall, it is sufficient for an agent to understand what it will get and how to configure the condition.
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 description adds value beyond the schema by explaining metric-specific window requirements ('needs window 1h|24h|7d' for price_change_pct) and confirming the operator set. It also clarifies that all metrics are hourly-resolution counts. Schema coverage is 50% (window, preimage, payment_hash have descriptions), so the description compensates for missing semantics on metric, op, and value by providing context.
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: 'Counts, at hourly resolution, how often a single condition became true in the trailing 90 days'. It specifies the resource (condition frequency) and scope (90-day trailing window), distinguishing it from sibling tools like btcmatic_radar which likely focuses on current conditions. The 'Past frequency, not a forecast' clarification removes ambiguity.
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 historical analysis ('Past frequency') and warns against using it for predictions, but it does not explicitly say when to choose this over alternatives like btcmatic_radar or btcmatic_context. There is no direct comparison or exclusionary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Latest BTC price with 1h/24h/7d change, next-block fee (sat/vB) with its percentile over the trailing 90 days of hourly averages, and mempool size. Values older than 5 minutes come back null; missing history is reported in data_quality, never interpolated. Descriptive only.
| Name | Required | Description | Default |
|---|---|---|---|
| preimage | No | The preimage your wallet showed after paying the bolt11 from the offer | |
| payment_hash | No | From a previous 402 offer (with preimage) — proof of a settled per-call payment |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behavioral aspects: stale data older than 5 minutes returns null, missing history is reported in data_quality (never interpolated), and the tool is 'Descriptive only.' These are valuable details that help the agent understand edge cases. It does not cover payment/auth requirements explicitly, but the 'paid' title and parameter names imply that, so the description adds meaningful context beyond the schema.
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, concise and front-loaded. It lists the core data returned in the first sentence and important caveats in the second. No fluff or repetition—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 simple market data tool, the description is complete. It enumerates all returned fields (price, changes, fee, percentile, mempool size) and explains data quality handling. There is no output schema, but the description sufficiently clarifies expectations. The tool is simple enough that no additional context is required.
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 each parameter (preimage and payment_hash) having a description. The tool description does not add additional parameter semantics beyond what the schema already provides. Since the schema covers all parameter meanings adequately, the baseline of 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 specifies the tool's function: it returns the latest BTC price with 1h/24h/7d change, next-block fee percentile, and mempool size. This is a specific verb-resource pair that distinguishes it from sibling tools like btcmatic_discover (which likely focuses on discovery) and btcmatic_radar (radar-specific). The scope is unambiguous.
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 retrieving current Bitcoin market context and states it is 'Descriptive only' (read-only). However, it does not explicitly mention when to use it vs. alternatives like btcmatic_radar or btcmatic_condition_frequency. The guidance is implicit through the tool's purpose, but no exclusions or comparisons are given, so it does not fully meet the bar for explicit usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Free. The balance behind the configured prepaid token (BTCMATIC_AGENT_TOKEN) and how many calls it still covers.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No | Override the configured token |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It does disclose that the operation is free and what it returns, but it does not explicitly state that it is read-only or describe any side-effect-free behavior.
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 only two short sentence fragments, front-loaded with the most important fact (free) followed by a clear purpose statement. Every word earns its place with no redundancy.
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 simple tool with one optional parameter and no output schema, the description covers the essential purpose, cost, and return value (remaining calls). It is complete enough for an agent to invoke it correctly, though it could mention relationship to topup tools.
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 is 100% for the single optional 'token' parameter, which already has a description ('Override the configured token'). The tool description adds no additional parameter semantics 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?
The description states the tool returns the balance behind the configured prepaid token and how many calls it covers. This clearly differentiates it from the sibling topup tools, though it lacks an explicit verb like 'check' or 'get'.
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 says 'Free' but gives no explicit guidance on when to use this tool versus the topup siblings. There is no mention of checking balance before topping up or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Free. What the BTCMatic agent API offers, what one call costs in sats, the prepaid bounds and the payment flow. Call this first.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks explicit behavioral details beyond what it does. It mentions 'Free' but does not elaborate on side effects, rate limits, or other behavioral traits. With no annotations provided, the description carries the burden, but it does not go beyond a basic overview. However, it does add context on the payment flow, which is somewhat behavioral.
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 highly concise, using a single sentence with key bullet points, and the imperative 'Call this first' is front-loaded. Every word earns its place, and it is structured effectively.
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 that the tool is a discovery/informational endpoint with zero parameters and no output schema, the description covers the essentials: what is offered, cost, bounds, and flow. It is complete enough for the agent to invoke it without further clarification.
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 0 parameters, and the schema is empty, so the description is the only source of meaning. It adequately explains what the tool offers given that no parameters are needed. The baseline for zero parameters is 4, and the description meets it without unnecessary details.
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 what the tool does: it provides an overview of the BTCMatic agent API, including costs, prepaid bounds, and payment flow. It distinguishes itself from siblings by positioning itself as the first call to understand the API's usage and economics.
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 instructs to 'Call this first,' establishing a clear ordering relative to other tools. It also sets expectations for what information will be obtained (costs, bounds, payment flow), which guides the agent on when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Open and corroborated self-custody security incidents (hardware/software wallets, nodes, payment stacks), per-product feed chatter counts with the number of distinct sources behind them, and the per-source precision ledger from manually labeled items. Counts and labels only — no verdicts. Costs one call; without payment the 402 offer is returned as data.
| Name | Required | Description | Default |
|---|---|---|---|
| product | No | Filter, e.g. "wallet:coldcard" | |
| preimage | No | The preimage your wallet showed after paying the bolt11 from the offer | |
| payment_hash | No | From a previous 402 offer (with preimage) — proof of a settled per-call payment |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries behavioral disclosure. It explicitly states it costs one call, returns a 402 offer as data if unpaid, and clarifies that it only provides counts/labels, not verdicts. This adds meaningful behavioral context beyond what any schema would imply, though it does not explicitly state whether it is read-only.
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 concise and well-structured: one sentence summarizing the data content, one sentence covering payment and failure behavior. No filler or redundancy, and the most important aspects (data type, payment requirement) are 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 there is no output schema, the description adequately covers what the tool returns (incidents, chatter counts, precision ledger) and the payment condition. It also implies how to satisfy payment (via preimage/payment_hash in schema). While not exhaustive, it is complete enough for an agent to understand the tool's purpose and invocation, especially with the 100% parameter documentation.
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 parameters are already documented. The tool description does not add additional meaning about parameters or their usage beyond what the schema provides. The baseline of 3 is appropriate because the schema carries the full burden and the description adds no extra value.
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 a security radar snapshot: open/corroborated incidents, chatter counts with source counts, and a precision ledger. It distinguishes itself from siblings by focusing on security radar data and explicitly notes it returns counts/labels, not verdicts, which differentiates it from other btcmatic tools like discovery or context.
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 context by stating what data it returns and that it's a paid snapshot, but it does not explicitly mention when to use it instead of sibling tools. It provides clear context on the tool's function, but lacks direct exclusions or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Free. Mints a Lightning invoice for a prepaid balance (see btcmatic_discover for the min/max). Pay it with a wallet you control, then call btcmatic_topup_claim with the preimage. The payment hash alone never yields a token.
| Name | Required | Description | Default |
|---|---|---|---|
| amount_sats | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. It states it's 'Free' and explains the redemption flow, but does not detail potential failure modes, expiry, or what happens if payment isn't claimed - though the core behavior is disclosed.
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, front-loaded with key fact 'Free', and no redundant or filler content. Every sentence adds useful 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 a single parameter, no output schema, and no annotations, the description covers the essential behavior, flow, and link to discovery tool. It could mention edge cases or expiration, but for a simple invoice minting tool it is fairly 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?
With only one parameter and 0% schema coverage, the description doesn't explicitly explain amount_sats beyond referring to min/max via btcmatic_discover. It implies the amount is in satoshis but doesn't add much detail, though the simple schema plus reference to limits provides moderate base.
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 tool mints a Lightning invoice for a prepaid balance, which is a specific verb+resource action. It also references btcmatic_discover for min/max, distinguishing it from other btcmatic tools.
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?
It explains the usage flow: pay with a wallet you control, then call btcmatic_topup_claim with the preimage. It clearly contrasts with the sibling claim tool and warns that the payment hash alone never yields a token, providing contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Proves the top-up payment with its preimage and receives the prepaid token EXACTLY ONCE. Store it and restart this server with BTCMATIC_AGENT_TOKEN= so every paid tool debits the balance automatically.
| Name | Required | Description | Default |
|---|---|---|---|
| preimage | Yes | ||
| payment_hash | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the exactly-once guarantee, the side effect of resuming/restarting the server, and the environment variable requirement. Without readOnly/destructive annotations, the description itself bears this weight, but it does not mention permissions, rollback, or other behavioral consequences.
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?
It consists of two dense but useful sentences and a collateral instruction. Every word contributes; no fluff. Well formatted.
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?
There is no output schema, no description of a return value, and not much context for the cryptographic token value or exceptions. Task states input requirements but not output. It also relies on an operational detail (surcharge) but not the actual meaning of a state restoration.
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 parameters (preimage, payment_hash) with regex patterns but no descriptions. The description only reluctantly refers to them as 'payment preimage' and 'payment hash', adding little value beyond the schema. There are no defaults or types. With <50% schema coverage, information is scarce.
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 ('proves'), identifies the resource (a paid top-up as a bearer token), and details unique behavior: the prepayment is proven via its hahs preimage, and the token is received exactly once. The wording 'EXACTLY ONCE' and 'store it' distinguishes this claim operation from sibling tools, but it does not explicitly name itself a top-up claim operation or contrast with alternatives.
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?
It establishes usage context by explaining that claiming the token precedes restarting the server with the agent token so that all paid tools automatically debit the balance. It does not, however, explicitly state when to use this instead of a sibling tool or include exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0btcmatic_condition_frequencybtcmatic_contextbtcmatic_creditsbtcmatic_discoverbtcmatic_radarbtcmatic_topupbtcmatic_topup_claimScored across 7 tools
Each tool addresses a distinct concern: discovery, security radar, market context, historical condition frequency, pre-payment minting, token claiming, and balance checks. There is no overlap or ambiguity between them; even the related topup and topup_claim are clearly stage-separated.
All tools share the 'btcmatic_' prefix, but the second part mixes nouns (radar, context, credits) and verbs (discover, topup_claim). The pattern is predictable and readable, but not a strict verb_noun convention, so it loses a point for minor stylistic inconsistency.
Seven tools is well within the ideal range for a focused MCP server. Each tool earns its place covering the API's core functions (information, data, condition analysis, payment lifecycle, and account status) without redundancy or bloat.
The tool surface covers the full lifecycle: discovery, market data, historical condition analysis, the prepaid payment flow (mint, claim, balance), and security radar. There are no obvious missing operations that would hinder an agent's ability to accomplish the server's intended tasks.
Pay-per-action access to APIs and MCP tools over Lightning L402 and Base USDC x402.
Pay-per-call DeFi and macro intel for AI agents. x402 USDC tools via streamable HTTP /api/mcp.
Pay-per-call ($0.005–$0.03 USDC) market, on-chain, and prediction-market data API for AI agents and trading bots via the x402 protocol — no signup, no API key. Exposed as a remote MCP server with 15 tools: pre-trade token security (honeypot/liquidity checks), kimchi premium, funding rate APR, DEX slippage, Polymarket arbitrage & liquidity audits, and Hyperliquid HIP-4 prediction-market odds.
Bitcoin intelligence API. Pay per call via L402 Lightning (10-200 sats). No accounts needed.
