MCP-сервер, предоставляющий доступ к API аналитики рынков прогнозов Storm для любого клиента Model Context Protocol.
Storm — это автономный ИИ-агент, управляющий Eyewall Markets, сервисом аналитики рынков прогнозов, охватывающим Polymarket, Kalshi, Manifold, Futuur, Betfair, ForecastEx и другие площадки. Этот пакет представляет собой легкий MCP-мост через stdio, который позволяет LLM-клиентам — Claude Desktop, Claude Code, Cursor, Zed и любому другому хосту с поддержкой MCP — считывать канонические события Storm, кросс-площадочные спреды, каталог площадок и входящие оповещения пользователя в виде нативных вызовов инструментов.
Он предназначен для аналитиков, трейдеров и разработчиков агентов, у которых уже есть подписка Storm и которые хотят, чтобы их LLM-рабочее пространство видело то же, что и Storm.
API Storm доступен только подписчикам уровня Edge ($499/мес). Сгенерируйте свой
api_keyна странице https://eyewallmarkets.com/account. Более низкие уровни подписки не имеют доступа к API и будут получатьHTTP 403при каждом обращении к любому эндпоинту этого сервера.
API-ключи имеют формат stk_, за которым следуют 48 шестнадцатеричных символов (всего 52 символа), и привязаны к одной учетной записи. Относитесь к ним как к любым другим учетным данным.
Полная документация API находится по адресу https://eyewallmarkets.com/api/docs.
Related MCP server: pmxt-mcp
Отредактируйте файл конфигурации MCP для Claude Desktop и добавьте запись storm в раздел mcpServers:
{
"mcpServers": {
"storm": {
"command": "npx",
"args": ["-y", "@eyewallmarkets/storm-mcp"],
"env": {
"STORM_API_KEY": "stk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
}
}
}
}Путь в macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonLinux:
~/.config/Claude/claude_desktop_config.json· Windows:%APPDATA%\Claude\claude_desktop_config.json.
Перезапустите Claude Desktop. Семь инструментов storm_* должны появиться в списке инструментов в любом новом диалоге.
claude mcp add storm npx -- -y @eyewallmarkets/storm-mcpЗатем экспортируйте API-ключ в среду, в которой Claude Code запускает сервер (или установите его в профиле вашей оболочки):
export STORM_API_KEY=stk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxТочный вызов CLI может отличаться в зависимости от версии Claude Code; см. официальную документацию по адресу https://docs.claude.com/en/docs/claude-code/mcp для получения канонической формы (включая способы передачи переменных окружения непосредственно в строке mcp add).
После установки выполните /mcp внутри Claude Code, чтобы убедиться, что сервер storm подключен и семь инструментов зарегистрированы.
Cursor считывает определения MCP-серверов из файла ~/.cursor/mcp.json. Добавьте ту же структуру, что используется для Claude Desktop:
{
"mcpServers": {
"storm": {
"command": "npx",
"args": ["-y", "@eyewallmarkets/storm-mcp"],
"env": {
"STORM_API_KEY": "stk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
}
}
}
}Перезагрузите интеграцию MCP в Cursor (Settings → MCP → Refresh).
Zed настраивает MCP-серверы в разделе assistant.context_servers в файле ~/.config/zed/settings.json:
{
"assistant": {
"context_servers": {
"storm": {
"command": "npx",
"args": ["-y", "@eyewallmarkets/storm-mcp"],
"env": {
"STORM_API_KEY": "stk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
}
}
}
}
}Перезапустите Zed или перезагрузите панель помощника.
Вся конфигурация осуществляется через переменные окружения, считываемые при запуске сервера.
Переменная | Обязательно | По умолчанию | Описание |
| да | — | API-ключ уровня Edge, формат |
| нет |
| Переопределение корня API. Полезно для стейджинга или локального сервера разработки. |
| нет |
| Тайм-аут запроса в миллисекундах. |
| нет |
| Один из уровней: |
Все семь инструментов доступны только для чтения и идемпотентны. Структура аргументов задокументирована ниже в формате, похожем на JSON-схему; актуальная схема — это то, что фактически видит MCP-клиент.
storm_list_eventsСписок канонических (кросс-площадочных) событий. С пагинацией на основе курсора.
{
"limit": { "type": "integer", "default": 50, "max": 200 },
"cursor": { "type": "string", "optional": true },
"category": { "type": "string", "optional": true, "example": "politics" },
"status": { "type": "string", "optional": true, "enum": ["open", "closed", "resolved"] }
}Пример запроса: "Перечисли следующие 20 открытых политических событий на Storm."
storm_get_eventПолучение одного события по слагу, включая все связанные исходы и цены по каждой площадке.
{
"slug": { "type": "string", "required": true, "example": "us-pres-2028" }
}Пример запроса: "Получи полную запись Storm для us-pres-2028 и скажи мне, у какого исхода самый широкий кросс-площадочный спред."
storm_list_spreadsСписок недавних кросс-площадочных спредов, где чистая прибыль (после комиссий) превышает порог. Отсортировано по убыванию прибыли (edge DESC).
{
"min_edge_bps": { "type": "integer", "default": 100 },
"limit": { "type": "integer", "default": 50, "max": 200 },
"cursor": { "type": "string", "optional": true }
}Пример запроса: "Покажи мне топ-10 спредов Storm с прибылью не менее 250 б.п. прямо сейчас."
storm_get_marketПоиск одной записи площадки/рынка по (venue_slug, external_id).
{
"venue": { "type": "string", "required": true, "example": "polymarket" },
"external_id": { "type": "string", "required": true }
}Пример запроса: "Найди рынок Polymarket 0xabc... на Storm."
storm_list_venuesСписок всех площадок, отслеживаемых Storm, с указанием регуляторного статуса (зарегистрированные CFTC DCM, офшорные и т.д.), графиков комиссий и флагов возможностей (книга ордеров, AMM, пари-мутуэль).
{}Пример запроса: "Какие из отслеживаемых Storm площадок являются зарегистрированными CFTC DCM?"
storm_get_alerts_inboxОпрос входящих оповещений пользователя через api-канал. Подписчики Edge могут направлять оповещения в канал доставки api; этот инструмент очищает очередь неподтвержденных сообщений.
{
"since": { "type": "integer", "minimum": 0, "optional": true, "example": 4521 }
}Курсор — это целочисленный id последнего просмотренного вами оповещения. Передайте next_since из предыдущего ответа, чтобы получить только новые оповещения; пропустите, чтобы читать с сохраненного курсора подтверждений пользователя. Пример запроса: "Опроси мой входящий ящик Storm и суммируй все, что я не подтвердил."
storm_ack_alertsПродвижение постоянного курсора подтверждений, чтобы будущие опросы входящих сообщений пропускали уже обработанные оповещения. Курсор находится на стороне сервера и сохраняется между сессиями MCP.
{
"up_to": { "type": "integer", "minimum": 0, "required": true, "example": 4530 }
}Пример запроса: "Подтверди все оповещения Storm по текущий момент."
Пользователь: Найди мне все спреды Storm по выборам 2028 года с прибылью выше 300 б.п. и назови топ-3.
Помощник: (вызывает
storm_list_spreadsсmin_edge_bps: 300, limit: 50, фильтрует ответ по префиксу слага события2028_us_presidential_, затем вызываетstorm_get_eventдля топ-3 для обогащения данных)Возвращает три самых широких открытых спреда по выборам 2028 года, пару площадок с каждой стороны и информацию о том, на какой площадке находится более выгодная цена.
Пользователь: Опроси мой входящий ящик Storm и суммируй неподтвержденные оповещения, затем подтверди все, что ты суммировал.
Помощник: (вызывает
storm_get_alerts_inboxбезsince, суммирует элементы по категориям, затем вызываетstorm_ack_alertsсup_to, установленным на самый большой увиденныйid)Возвращает категоризированное резюме неподтвержденных оповещений (пересечения спредов, изменения статуса площадок, события разрешения) и подтверждает продвижение курсора, чтобы последующие опросы возвращали только новые элементы.
API Storm на стороне сервера ограничивает количество запросов до 10 запросов в секунду на API-ключ. Если вы превысите этот лимит, сервер вернет HTTP 429 с заголовком Retry-After: 1. Этот MCP-мост не выполняет повторные попытки автоматически; он выводит ошибку для LLM в виде обычного текстового содержимого в результате инструмента, чтобы модель могла решить, стоит ли подождать, повторить попытку или сдаться.
Ошибки возвращаются LLM в таком виде (текстовое содержимое в результате инструмента, isError: true):
Storm API error (HTTP 429, rate_limited): too many requests Retry after 1000 ms.Storm API error (HTTP 403, edge_tier_required): edge_tier_requiredStorm API error (HTTP 401, invalid_credentials): invalid_credentialsСбои на сетевом уровне (DNS, TCP, TLS, тайм-аут) отображаются как:
Storm API error (HTTP 0, transport): request timeoutПолный HTTP-статус, код ошибки Storm и человекочитаемое сообщение всегда включены, чтобы LLM могла действовать на их основе.
git clone https://github.com/lsudduth/storm-mcp.git
cd storm-mcp
npm install
npm testУкажите локальный сервер разработки Storm, переопределив базу API:
STORM_API_BASE=http://localhost:8080/api/v1 \
STORM_API_KEY=stk_dev_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx \
node src/index.mjsСервер использует stdio MCP, поэтому вы можете управлять им напрямую с помощью любого тестового инструмента MCP или передавая кадры JSON-RPC вручную.
Тесты используют встроенный тестовый раннер Node; без Jest, без Vitest, без транспилятора.
MIT — см. LICENSE.
© 2026 XCH1TB, LLC dba Eyewall Markets.
Сам Storm — автономный ИИ-агент, который управляет Eyewall Markets и создает данные, предоставляемые этим сервером, — является отдельной внутренней кодовой базой. Этот пакет является лишь клиентским MCP-мостом к публичному API Storm, доступному только для чтения.
Это программное обеспечение и данные, которые оно предоставляет, предназначены только для информационных целей. Ничто из того, что возвращает Storm или этот MCP-сервер, не является юридической, финансовой, налоговой или инвестиционной консультацией. Участие в рынках прогнозов регулируется вашим местным законодательством и собственными правилами участия площадки; в частности, Polymarket ограничен в Соединенных Штатах в соответствии с распоряжениями CFTC и недоступен для большинства лиц из США. Право на участие в площадке — это ваша ответственность, а не Storm или этого сервера. Storm агрегирует публично наблюдаемое состояние рынка и не совершает сделки от вашего имени.
Advance the persistent ack cursor to the given sequence id, removing items at or below it from the api-channel inbox. Call this after the LLM / agent has processed items returned by storm_get_alerts_inbox; otherwise the same items will keep being returned. Sourced from Eyewall Markets / Storm. The cursor is server-side and survives across MCP sessions.
| Name | Required | Description | Default |
|---|---|---|---|
| up_to | Yes | Ack all alerts with sequence id <= up_to. Use the highest id seen in storm_get_alerts_inbox. |
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 that the cursor is persistent, server-side, survives sessions, and that items are removed. This is sufficient for a mutation tool of this complexity.
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 cover action, usage, and persistence. Every sentence adds necessary information with no redundancy or filler.
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 acknowledgment tool with one parameter and no output schema, the description covers behavior, usage context, and parameter guidance. Minor gap: does not mention any potential side effects, but overall 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 coverage is 100% and schema already describes the parameter. The description adds value by advising to use the highest id seen in storm_get_alerts_inbox, which is practical guidance beyond the raw schema definition.
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 ('advance the persistent ack cursor' and 'removing items') and the resource ('api-channel inbox'). It distinguishes itself from the sibling tool storm_get_alerts_inbox by focusing on acknowledgment and removal.
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 explicitly instructs to call this after processing items from storm_get_alerts_inbox to avoid duplicates. It provides clear context on when to use, though it does not elaborate on when not to use or list alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Poll the subscriber's api-channel notification inbox for cross-venue price-difference and event notifications that haven't been ack'd yet. Each item is a descriptive notification — it names the canonical event, the two venues, the prices each venue was publishing at the observation timestamp, and the rule that matched. Sourced from Eyewall Markets / Storm. Pass the next_since returned by the previous call as since to get only newer items. After processing, call storm_ack_alerts to advance the persistent cursor.
| Name | Required | Description | Default |
|---|---|---|---|
| since | No | Only return alerts with sequence id strictly greater than this. Defaults to 0 (full inbox). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of explaining behavior. It states that the tool returns unacknowledged notifications, explains cursor-based pagination, and implies a read-only operation. It does not mention rate limits or other details, but the core behavioral traits are well covered.
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 at three sentences, each serving a distinct purpose: purpose explanation, content description, and usage pattern with next steps. No unnecessary 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?
Given the tool's simplicity (one parameter, no output schema, no annotations) and the complexity of the polling pattern, the description is fully complete. It explains the tool, pagination, and the required follow-up action, leaving no critical gaps.
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 'since' is fully described in the schema (100% coverage), and the description adds significant value by explaining its role in pagination and instructing how to use the 'next_since' value from previous calls. This goes beyond the schema's basic constraint.
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 purpose: to poll the subscriber's api-channel notification inbox for unacknowledged cross-venue price-difference and event notifications. It names the verb 'poll', the resource 'inbox', and details the content of each notification, distinguishing it from the related 'storm_ack_alerts' tool.
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 explicit guidance on pagination (using 'next_since' from previous call as 'since') and directs users to call 'storm_ack_alerts' after processing to advance the cursor. While it doesn't explicitly state when not to use the tool, the context is clear and the alternative is named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch a single canonical event by its Storm slug, including the full set of cross-venue markets attached to that event and each venue's currently published price. Use after storm_list_events when you need the canonical question text, resolution criteria, and per-venue market handles. Sourced from Eyewall Markets / Storm; describes the published-price observation, not a buy or sell recommendation.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Storm event slug, e.g. 'will-fed-cut-rates-by-2026-q3'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description implies read-only fetch and adds context that data is observational, not advisory. However, it does not disclose any side effects, auth needs, or limitations beyond that.
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 succinct sentences: first defines action and scope, second provides usage guidance and disclaimer. No redundant text; all information is relevant 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?
Given the simple input and lack of output schema, the description covers core purpose, usage context, and key outputs (question text, resolution criteria, market handles). Missing exact response structure but acceptable for this complexity.
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% with a well-described parameter. The description does not add significant meaning beyond the schema, so a 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 states the tool fetches a single canonical event by slug, including markets and prices. It distinguishes from sibling 'storm_list_events' by specifying it's for detailed event data after listing.
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 suggests using after storm_list_events and states the need for canonical question text, resolution criteria, and market handles. Includes disclaimer that it's observation, not a recommendation, but does not explicitly mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch the canonical Storm view of a single market on a specific venue, including the venue's currently published bid/ask, volume, and the canonical event it's joined to. Use when you have a venue + the venue's native market id (e.g. a Kalshi ticker or Polymarket condition id) and want Storm's normalized representation. Sourced from Eyewall Markets / Storm; describes published price snapshots from the venue's public read endpoints, not a recommendation.
| Name | Required | Description | Default |
|---|---|---|---|
| venue | Yes | Venue slug, e.g. 'kalshi' or 'polymarket'. See storm_list_venues. | |
| external_id | Yes | The venue's native market identifier (Kalshi ticker, Polymarket condition id, etc.). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description states it fetches from public read endpoints and is not a recommendation, indicating a safe read operation. Could mention if real-time or cached, but still good.
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 purpose, no unnecessary words. Efficiently conveys all essential 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 no output schema, description adequately covers return fields (bid/ask, volume, canonical event) and notes it's not a recommendation. Sufficient for simple two-parameter 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?
Schema description coverage is 100% with clear explanations for venue and external_id. The description reinforces the usage but doesn't add significant new constraints or examples beyond 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 clearly states the tool fetches the canonical Storm view of a single market, including bid/ask, volume, and associated event. It distinguishes itself from sibling tools like storm_list_events and storm_get_event.
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 'Use when you have a venue + the venue's native market id', providing clear conditions. Also references storm_list_venues for obtaining the slug, guiding the agent on prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List canonical prediction-market events (questions/topics) tracked by Eyewall Markets / Storm across the public venues it covers (Kalshi, Polymarket, Manifold, ForecastEx, and others). Use this to discover what events exist before drilling into a specific event with storm_get_event. Supports filtering by category (e.g. 'politics', 'economics') and status (e.g. 'open', 'resolved'), and is cursor-paginated. Read-only market reference data; describes the event ontology, not a recommendation.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Page size (1-100). Default server-side is typically 25. | |
| cursor | No | Opaque pagination cursor returned in next_cursor from a previous call. | |
| category | No | Filter to a single category slug, e.g. 'politics'. | |
| status | No | Filter by event status, e.g. 'open' or 'resolved'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description declares 'Read-only market reference data' and mentions cursor-pagination. Lacks details on rate limits or auth, but sufficient for basic safety.
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?
Four sentences, front-loaded with purpose, each sentence adds value (use case, filtering, pagination, read-only nature). 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?
No output schema, but description mentions cursor-paginated results. Could specify return fields, but adequate for discovering events before drilling down.
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%, so baseline is 3. Description adds examples for category and status, but no deeper semantics beyond schema descriptions.
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?
Description clearly states the tool lists prediction-market events with specific venues (Kalshi, Polymarket, etc.), uses the verb 'list' and resource 'events', and distinguishes from sibling tool storm_get_event.
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 'Use this to discover what events exist before drilling into a specific event with storm_get_event', providing a clear use case and alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List recent cross-venue published-price observations — pairs of markets on different venues that are publishing different prices for the same canonical outcome. Returns rows whose published-price difference net of each venue's posted fees clears the configured floor, ordered by net_edge_bps DESC. Sourced from Eyewall Markets / Storm. Descriptive market-data only: each row reports what each venue is publishing, not a buy or sell recommendation, and does not warrant fillable depth at any price reported.
| Name | Required | Description | Default |
|---|---|---|---|
| min_edge_bps | No | Minimum published-price difference net of venue fees, in basis points (1 bp = 0.01%). E.g. 50 returns only rows whose net_edge_bps is >= 50. Defaults to the server-side floor. | |
| limit | No | Page size (1-100). | |
| cursor | No | Opaque pagination cursor returned in next_cursor from a previous call. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavioral traits: lists recent observations, filters by configured floor, orders by net_edge_bps descending, and emphasizes that data is descriptive and non-actionable. This covers safety and operational expectations.
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 extremely concise—two sentences that front-load the primary purpose in the first sentence and add behavioral caveats in the second. No extraneous words 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 tool's moderate complexity (3 parameters, no output schema), the description covers key aspects: what is returned, ordering, and behavioral constraints. However, it does not mention pagination handling (cursor/next_cursor) explicitly, leaving that to the schema.
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%, but the description adds value by explaining min_edge_bps with an example and mentioning server-side floor default. However, for 'limit' and 'cursor', no additional semantic context is provided beyond 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 clearly states the verb 'List' and the resource 'cross-venue published-price observations', and distinguishes this tool from siblings like storm_list_events and storm_list_venues by specifying its unique function of identifying pricing disparities between venues.
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 explicitly states the tool's purpose and clarifies that it provides descriptive market data only, not buy/sell recommendations or depth warranties. However, it does not explicitly mention when not to use this tool or provide direct alternatives beyond sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all public prediction-market venues covered by Eyewall Markets / Storm, with their slugs, display names, regulatory posture (CFTC-registered DCM, offshore, etc.), posted fee schedules, capability flags (orderbook / AMM / parimutuel), and current ingestion status. Call this first when you need the venue slug to pass to storm_get_market. Reference data only — venue eligibility for any individual user is governed by the venue and the user's local law.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 tool is reference data only and lists the kind of data returned, which is sufficient for a read-only tool with no side effects.
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 action and output, every sentence adds value without 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?
With no output schema, the description thoroughly enumerates return fields (slugs, display names, regulatory posture, etc.) and clarifies it's reference data, making it complete for agent use.
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 baseline is 4. The description adds meaning by explaining what the output contains, compensating for 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 action ('List all public prediction-market venues') and specifies the output fields, distinguishing it from siblings like storm_get_market which needs a slug.
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 'Call this first when you need the venue slug to pass to storm_get_market', providing clear when-to-use guidance and noting that eligibility is governed by venue and local law.
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.
v0.1.2storm_ack_alertsstorm_get_alerts_inboxstorm_get_eventstorm_get_marketstorm_list_eventsstorm_list_spreadsstorm_list_venuesScored across 7 tools
Each tool targets a distinct action or resource: acking alerts, polling inbox, fetching events/markets, listing events/spreads/venues. No two tools have overlapping purposes, and descriptions clearly differentiate them.
All tools follow a consistent 'storm_verb_noun' pattern in snake_case, with verbs like ack, get, list. This makes it easy for an agent to infer functionality from names.
7 tools is a well-scoped set for a prediction market data server. Each tool serves a necessary function without unnecessary duplication or gaps, covering discovery, detailed queries, and notification management.
The tool set covers the full lifecycle: discovering events (list), drilling into details (get), accessing markets (get), monitoring spreads and alerts, acknowledging alerts, and listing venues. No obvious missing operations for the stated purpose.
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