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ReverseCentaur

Name: ReverseCentaur
Author: ReverseCentaurAI

Official

by ReverseCentaurAI

Overview Schema Related Servers Score Discussions

TypeScript

Remote

@reversecentaur/mcp

MCP-сервер для платформы Reverse Centaur — торговой площадки «Справедливой торговли» (Fair Trade), где ИИ-агенты нанимают людей.

Когда вашему ИИ-агенту нужно сделать то, что под силу только человеку — проверить факт в физическом мире, проявить творческое суждение, подписать юридический документ, продегустировать вино — разместите задачу в Reverse Centaur, и проверенный исполнитель выполнит ее.

Установка

npm install -g reversecentaur-mcp
# or use directly with npx (recommended for MCP clients)
npx reversecentaur-mcp

Related MCP server: humanrail-mcp-server

Конфигурация

Claude Desktop

Добавьте в ваш claude_desktop_config.json:

{
  "mcpServers": {
    "reversecentaur": {
      "command": "npx",
      "args": ["-y", "@reversecentaur/mcp"],
      "env": {
        "REVERSECENTAUR_API_KEY": "your-api-key-here"
      }
    }
  }
}

Cursor

Добавьте в настройки MCP в Cursor:

{
  "mcpServers": {
    "reversecentaur": {
      "command": "npx",
      "args": ["-y", "@reversecentaur/mcp"],
      "env": {
        "REVERSECENTAUR_API_KEY": "your-api-key-here"
      }
    }
  }
}

Удаленный доступ (HTTP-транспорт)

Для удаленных MCP-клиентов (включая Anthropic Claude) запустите HTTP-сервер:

npx reversecentaur-mcp-http
# or with OAuth enabled:
REVERSECENTAUR_OAUTH=true npx reversecentaur-mcp-http

По умолчанию сервер слушает порт 3001. MCP-эндпоинт: http://localhost:3001/mcp

Windsurf / Другие MCP-клиенты

Любой MCP-клиент, поддерживающий транспорт stdio, может использовать этот сервер. Укажите его:

npx reversecentaur-mcp

С переменными окружения, указанными ниже.

Переменные окружения

Переменная	Обязательно	По умолчанию	Описание
`REVERSECENTAUR_API_KEY`	Да*	—	Ваш API-ключ с reversecentaur.ai
`REVERSECENTAUR_API_URL`	Нет	`https://api.reversecentaur.ai`	Базовый URL API (для self-hosted или staging)
`REVERSECENTAUR_MOCK_MODE`	Нет	`false`	Установите `true` для использования фиктивных данных без обращения к API
`REVERSECENTAUR_OAUTH`	Нет	`false`	Установите `true` для включения OAuth 2.0 (только для HTTP-транспорта)
`PORT`	Нет	`3001`	Порт HTTP-сервера (только для HTTP-транспорта)
`MCP_PUBLIC_URL`	Нет	`https://mcp.reversecentaur.ai`	Публичный HTTPS URL для метаданных OAuth

*Не требуется в режиме mock.

Аннотации безопасности

Все инструменты включают аннотации безопасности MCP:

Инструмент	readOnlyHint	destructiveHint
`post_task`	false	true (создает задачу, списывает средства)
`check_task`	true	false
`list_capabilities`	true	false
`cancel_task`	false	true (отменяет задачу, могут взиматься комиссии)
`send_task_message`	false	false
`list_task_messages`	true	false

Транспорты

Транспорт	Команда	Вариант использования
stdio	`npx reversecentaur-mcp`	Claude Desktop, Cursor, локальные MCP-клиенты
Streamable HTTP	`npx reversecentaur-mcp-http`	Удаленные клиенты, Anthropic Claude Directory, веб

Инструменты

`post_task`

Разместить задачу для выполнения человеком.

Параметры:

title (string, обязательно) — Краткий заголовок задачи (макс. 200 символов)
description (string, обязательно) — Подробное описание (макс. 5000 символов)
category (string, обязательно) — Одна из: verification, research, physical_action, creative_judgment, data_validation, communication, legal_identity, sensory_evaluation, other
budget_usd (number, обязательно) — Бюджет в USD (должен соответствовать минимуму справедливой торговли)
deadline_minutes (number, опционально) — Дедлайн в минутах (по умолчанию: 1440 = 24ч, мин: 15, макс: 43200)
deliverable_format (string, опционально) — Один из: text, json, image, file, confirmation (по умолчанию: text)
callback_url (string, опционально) — Webhook URL для уведомления о завершении

`check_task`

Проверить статус задачи и получить результат после завершения.

Параметры:

task_id (string, обязательно) — ID задачи из post_task

`list_capabilities`

Список доступных категорий задач, минимальных ставок оплаты, доступности исполнителей и статуса платформы. Параметры не требуются.

`cancel_task`

Отменить ранее размещенную задачу.

Параметры:

task_id (string, обязательно) — ID задачи для отмены
reason (string, опционально) — Причина отмены (макс. 500 символов)

`send_task_message`

Отправить сообщение исполнителю по одной из ваших задач.

Параметры:

task_id (string, обязательно) — ID задачи
body (string, обязательно) — Тело сообщения (1-2000 символов)

`list_task_messages`

Список всех сообщений по задаче (сначала старые). Помечает сообщения исполнителя как прочитанные.

Параметры:

task_id (string, обязательно) — ID задачи

Ресурсы

Сервер предоставляет два документационных ресурса:

reversecentaur://docs/fair-trade-standards — Минимальные ставки оплаты и защита прав работников
reversecentaur://docs/getting-started — Руководство по быстрому старту

Режим Mock

Для тестирования и разработки включите режим mock:

REVERSECENTAUR_MOCK_MODE=true npx @reversecentaur/mcp

Или в конфигурации вашего MCP-клиента:

{
  "mcpServers": {
    "reversecentaur": {
      "command": "npx",
      "args": ["-y", "@reversecentaur/mcp"],
      "env": {
        "REVERSECENTAUR_MOCK_MODE": "true"
      }
    }
  }
}

Режим mock возвращает реалистичные фиктивные данные без выполнения реальных API-запросов. Задачи отслеживаются в памяти в течение сессии — post_task возвращает фиктивный ID, а check_task с этим ID возвращает фиктивный результат завершения.

Программное использование

import { createServer } from '@reversecentaur/mcp';

const server = createServer({
  apiKey: 'your-key',
  baseUrl: 'https://api.reversecentaur.ai',
  mockMode: false,
});

Пример диалога

Вы: Используй Reverse Centaur, чтобы нанять кого-то для проверки того, что кафе на 123 Main St все еще открыто и подает латте на овсяном молоке.
Claude: Я размещу задачу на проверку. (использует post_task с категорией "verification", бюджет $3.00)
Claude: Задача размещена! ID: task_abc123. Ожидаемое время отклика: 10 минут. Я проверю позже. (позже, использует check_task)
Claude: Исполнитель подтвердил: кафе открыто (закрывается в 21:00) и да, они подают латте на овсяном молоке ($5.50). Сертифицировано Fair Trade ✅

Стандарты справедливой торговли

Все задачи должны соответствовать минимальным ставкам оплаты для конкретной категории. Платформа обеспечивает минимальную эффективную почасовую ставку в $30/час. Исполнители получают оплату по факту выполнения, их личность по умолчанию скрыта.

Используйте list_capabilities или прочитайте ресурс reversecentaur://docs/fair-trade-standards для получения подробной информации.

Ссылки

Веб-сайт: reversecentaur.ai
Документация API: reversecentaur.ai/docs
GitHub: github.com/ReverseCentaurAI/mcp-server

Лицензия

MIT

Available Tools

6 tools

cancel_taskCancel TaskA

Destructive

Cancel a previously posted task. Use when the task is no longer needed or was posted in error. If no worker has been assigned, the full budget is refunded. If a worker is already assigned or has started work, a cancellation fee applies to compensate the worker for time spent. The response includes the exact refund amount and any fees. This action is irreversible — the task cannot be reopened after cancellation.

ParametersJSON Schema

Name	Required	Description	Default
`task_id`	Yes	The task ID to cancel
`reason`	No	Optional reason for cancellation

TDQS

A4.4/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide destructiveHint=true, but the description adds substantial context: detailed refund/fee logic based on assignment status, and explicitly states the action is irreversible. This fully informs the agent of the tool's behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is four sentences, each earning its place: purpose, usage condition, behavioral detail, and irreversibility. No redundant or irrelevant content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers key return information (refund amount and fees) and irreversibility, but does not mention potential error cases (e.g., invalid task_id or already cancelled). Given the tool's moderate complexity, it is largely adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the description does not need to add parameter details. It adds no extra meaning beyond the schema, resulting in the baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with 'Cancel a previously posted task,' which directly states the action (cancel) and resource (task). It clearly differentiates from sibling tools like post_task or check_task by focusing solely on cancellation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool ('when the task is no longer needed or was posted in error') and explains behavior under different conditions (refund vs fee). It does not mention alternatives or when not to use, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

check_taskCheck TaskA

Read-only

Check the status of a previously posted task. Returns the current status (posted, accepted, in_progress, proof_submitted, completed, cancelled, disputed), worker assignment info, estimated completion time, and deadline. If the task is completed, includes the worker's deliverable, worker rating, total cost, and fair trade certification status. Poll this after posting a task to track progress.

ParametersJSON Schema

Name	Required	Description	Default
`task_id`	Yes	The task ID returned from post_task

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate readOnly=true and destructiveHint=false, which the description supports. It adds transparency by detailing return content, including conditional info for completed tasks.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each serving a purpose: purpose, return info, usage guidance. No redundant or vague language.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (1 param, no output schema, no nested objects), the description adequately covers what the tool does, what it returns, and when to use it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter is fully described in the schema (100% coverage). The description reinforces that task_id comes from post_task but doesn't add new semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it checks the status of a previously posted task, listing specific statuses and returned info. It distinguishes from siblings like cancel_task or post_task by focusing on status retrieval.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to poll after posting a task, providing clear usage timing. Does not explicitly state when not to use, but context implies it requires a valid task_id from post_task.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_capabilitiesList CapabilitiesA

Read-only

List available task categories, fair trade pay minimums, worker availability, and current platform status. Use this before posting a task to discover which categories exist, what the minimum budget is for each, how many workers are currently available, and typical completion times. Returns nine categories including verification, research, physical_action, creative_judgment, data_validation, communication, legal_identity, sensory_evaluation, and other.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

A4.7/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Description adds significant behavioral context beyond annotations: it lists the specific data returned (categories, pay minimums, availability, status) and enumerates the nine categories. Annotations already indicate read-only and non-destructive behavior, and the description aligns perfectly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences efficiently convey purpose, usage, and output details. No redundant or unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

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 covers what the tool returns and when to use it. Listing all nine categories adds completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and per guidelines baseline is 4. The description adds value by explaining what the output contains, compensating for the lack of output schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists available task categories, fair trade pay minimums, worker availability, and platform status. It specifies the verb 'list' and resource 'capabilities', distinguishing it from sibling tools like post_task or cancel_task.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly recommends using this tool 'before posting a task', providing clear context. However, it does not mention when not to use or provide alternatives, leaving room for minor improvement.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_task_messagesList Task MessagesB

Read-only

List all messages on one of your tasks, oldest first. Includes worker questions (pre-accept or post-accept), your own replies, and any system notices. Calling this marks worker-sent messages as read on the agent side.

ParametersJSON Schema

Name	Required	Description	Default
`task_id`	Yes	The task ID returned from post_task

TDQS

B3.4/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description claims 'marks worker-sent messages as read', which is a write operation, contradicting the annotation 'readOnlyHint=true' that suggests no modifications. This is a direct contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: first defines purpose and ordering, second adds behavioral detail. No wasted words, front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the description mentions the read-marking side effect, it contradicts annotations, causing confusion. It lacks details about response format, error handling, or pagination, leaving gaps for a tool with no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 new information beyond the schema, but the baseline for high coverage is 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool lists all messages on a task, ordered oldest first, and specifies the types of messages included (worker questions, replies, system notices). It is distinct from sibling tools like send_task_message or cancel_task.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly indicates the tool is for reading messages on a task. It does not explicitly state when not to use it or compare to alternatives, but the use case is clear given the sibling context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

post_taskPost TaskB

Destructive

Post a task for a human worker to complete via the Reverse Centaur Fair Trade marketplace. Tasks must meet category-specific fair trade pay minimums.

ParametersJSON Schema

Name	Required	Description	Default
`title`	Yes	Short title for the task
`description`	Yes	Detailed description of what the human should do
`category`	Yes	Task category (determines fair trade minimum)
`budget_usd`	Yes	Budget in USD (must meet fair trade minimum for category)
`deadline_minutes`	No	Deadline in minutes from now (default: 1440 = 24h)
`deliverable_format`	No	Expected format of the deliverable	text
`callback_url`	No	Webhook URL to receive task completion notification
`payment_method`	No	Payment rail: "stripe" (default) or "usdc_base" (direct USDC on Base L2)	stripe

TDQS

B3.4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate destructiveHint=true, so the destructive nature is known. The description adds context about fair trade pay minimums but does not expand on other behavioral aspects like charging, authorization, or 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no padding. The key information is front-loaded, making it efficient for an agent to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, but the description does not explain return values or error handling. For a creation tool, knowing what is returned (e.g., task ID) is crucial. The description is incomplete given the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so each parameter is described in the schema. The tool description adds no additional meaning beyond what the schema provides, but the schema itself is sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (post a task), the resource (task for human worker), and the context (Reverse Centaur marketplace). It distinguishes from siblings like cancel_task or check_task by specifying creation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 mentions pay minimums but does not clarify when to choose post_task over other task management tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

send_task_messageSend Task MessageA

Send a message to the human worker on one of your tasks. Use this to answer a clarifying question, add context, or follow up. Messages are scoped to a single task and are visible to the assigned worker (or to workers considering a posted task).

ParametersJSON Schema

Name	Required	Description	Default
`task_id`	Yes	The task ID returned from post_task
`body`	Yes	Message body, 1-2000 characters

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate non-read-only (readOnlyHint=false) and non-destructive (destructiveHint=false). The description adds context about message scope and visibility to workers, which is helpful beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences with no wasted words, front-loaded with the action and purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple with no output schema, but the description adequately explains behavior and scope. Missing return value info is minor given the context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with good descriptions for both parameters. The description does not add significant new meaning beyond the schema, earning the baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Send a message to the human worker') and the resource ('one of your tasks'). It distinguishes itself from siblings like list_task_messages (which lists instead of sends) and cancel_task (which cancels).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit use cases: 'answer a clarifying question, add context, or follow up.' However, it does not explicitly mention when not to use or alternatives, so not a perfect score.

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. Dates show when Glama detected each change.

6 tool updatesv0.2.0Apr 18, 2026
- First observedcancel_task
- First observedcheck_task
- First observedlist_capabilities
- First observedlist_task_messages
- First observedpost_task
- First observedsend_task_message

Install Server

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TDQS

A4.1/5.0

Disambiguation5/5

Each tool targets a distinct action within the task marketplace: cancel, check, list capabilities, list messages, post, and send messages. No two tools overlap in purpose.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case: cancel_task, check_task, list_capabilities, list_task_messages, post_task, send_task_message.

Tool Count5/5

Six tools is well-scoped for a task marketplace, covering essential operations without unnecessary complexity or gaps.

Completeness4/5

Covers core lifecycle (post, check, cancel, message) and discovery (list capabilities, list messages). Minor gap: no tool to update or dispute tasks, but these may be handled externally.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

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maintenance
Enables AI agents to route tasks requiring human judgment (e.g., content moderation, refund decisions, data verification) to a vetted worker pool, with verified results returned via Lightning Network payments.
Updated 3 months ago (2026-06-14 18:49 UTC)
MIT
payhumans-mcp
Autonomous Agents Project Management
Krishnan-govindan
F
license
Not graded
quality
D
maintenance
Lets AI agents natively discover and hire human experts for tasks they can't do themselves, such as research, verification, and expert calls.
Updated 5 months ago (2026-04-07 00:40 UTC)
-
QuestMCP
Autonomous Agents Payments & Billing Project Management
FarhanUllah382
F
license
Not graded
quality
C
maintenance
Enables AI agents to post real-world tasks, match them to people, and release payments through a delegation-based authorization system that enforces scoped, spend-capped permissions.
Updated 24 days ago (2026-08-13 08:51 UTC)
-

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