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Wiro AI

Wiro AI

远程服务
wiro.ai其他5今天更新

关于 Wiro AI

Wiro AI 的 MCP 服务供 AI 助手用户查找并运行图像、视频、音频和 LLM 模型。它通过本地 stdio 服务或托管端点提供 13 个工具,包括任务跟踪和文档搜索。

主要功能

  1. 01搜索并推荐模型
  2. 02查看模型参数和价格
  3. 03运行并跟踪生成任务
  4. 04上传模型输入文件
  5. 05浏览任务历史并搜索文档

适用场景

  1. 01为媒体生成任务查找模型
  2. 02运行前核对模型参数和费用
  3. 03继续长时间生成任务或查看任务历史

MCP 相关

向 MCP 客户端提供 13 个模型发现、运行、文件上传、任务管理和文档搜索工具。客户端可连接本地 stdio 服务,也可连接 Wiro AI 托管的 streamable HTTP 端点。

配置

远程服务无需本地安装。选择你使用的客户端,复制配置或使用一键安装。

服务地址https://mcp.wiro.ai/v1
一键复制安装命令
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

命令在终端中运行;JSON 粘贴到对应客户端的 MCP 配置后重启。需要授权的服务会在首次连接时提示登录。

全部服务地址
Streamable HTTPhttps://mcp.wiro.ai/v1需要授权
安装包
npm@wiro-ai/wiro-mcp1.3.2

工具

README 原文English

来自项目 README

README 暂无中文译文,以下为英文原文;中文介绍见上方。

Wiro AI

Wiro MCP Server

Official MCP server for Wiro AI: search, price and run image, video, audio and LLM models from Cursor, Claude Code, Claude Desktop, Windsurf and any other MCP client.

npm Node.js 20+ MCP server License: MIT

Website · Models · Docs · Dashboard

Wiro AI koala mascot

@wiro-ai/wiro-mcp is a TypeScript Model Context Protocol server that runs locally over stdio with npx. Its 13 tools let an AI assistant search the Wiro AI model catalog, read a model's parameters and price, run it and wait for the result, upload input files, browse past tasks and search the Wiro AI docs. The hosted server at https://mcp.wiro.ai/v1 serves the same tools with nothing to install.

Quick Start

Local npx and library usage require Node.js 20 or later. The hosted MCP endpoint does not require a local Node.js installation.

1. Get API Keys

Sign up at wiro.ai and create a project at wiro.ai/panel/project/new to get your API key and secret.

2. Add to Your AI Assistant

Cursor: open MCP settings (Cmd+Shift+P → "Open MCP settings") and add:

{
  "mcpServers": {
    "wiro": {
      "command": "npx",
      "args": ["-y", "@wiro-ai/wiro-mcp"],
      "env": {
        "WIRO_API_KEY": "your-api-key",
        "WIRO_API_SECRET": "your-api-secret"
      }
    }
  }
}

Claude Code:

claude mcp add wiro -- npx -y @wiro-ai/wiro-mcp

Then set environment variables WIRO_API_KEY and WIRO_API_SECRET.

Claude Desktop: add to claude_desktop_config.json:

{
  "mcpServers": {
    "wiro": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@wiro-ai/wiro-mcp"],
      "env": {
        "WIRO_API_KEY": "your-api-key",
        "WIRO_API_SECRET": "your-api-secret"
      }
    }
  }
}

Windsurf: add to MCP settings:

{
  "mcpServers": {
    "wiro": {
      "command": "npx",
      "args": ["-y", "@wiro-ai/wiro-mcp"],
      "env": {
        "WIRO_API_KEY": "your-api-key",
        "WIRO_API_SECRET": "your-api-secret"
      }
    }
  }
}

OpenClaw: configure a remote server under mcp.servers:

{
  "mcp": {
    "servers": {
      "wiro": {
        "url": "https://mcp.wiro.ai/v1",
        "transport": "streamable-http",
        "connectionTimeoutMs": 10000,
        "headers": {
          "Authorization": "Bearer ${WIRO_MCP_AUTH}"
        }
      }
    }
  }
}

Set WIRO_MCP_AUTH in OpenClaw's environment to your API key, or to API_KEY:API_SECRET for a project with signature-based auth. Then verify with openclaw mcp doctor wiro --probe. On older OpenClaw releases without that probe command, use openclaw mcp show wiro, restart OpenClaw, and run /tools verbose.

Hermes: add to ~/.hermes/config.yaml:

mcp_servers:
  wiro:
    url: "https://mcp.wiro.ai/v1"
    headers:
      Authorization: "Bearer ${WIRO_MCP_AUTH}"
    timeout: 60
    connect_timeout: 10

Store WIRO_MCP_AUTH (your API key, or API_KEY:API_SECRET) in ~/.hermes/.env, then run /reload-mcp and /tools.

3. Start Using

Ask your AI assistant:

  • "Generate a photorealistic image of a mountain lake at sunset"
  • "What video generation models are available on Wiro?"
  • "Show me the parameters for google/veo3-1"
  • "Create a 5-second video with Kling V3: a drone shot over mountains"
  • "Check the status of my last task"
  • "Show my latest productions and open the newest result"

Authentication

Wiro AI supports two authentication types, chosen when you create a project:

Signature-Based (Recommended)

More secure. Requires both API key and API secret.

WIRO_API_KEY=your-api-key
WIRO_API_SECRET=your-api-secret
API Key Only

Simpler. Only requires the API key. Omit WIRO_API_SECRET from your config.

WIRO_API_KEY=your-api-key

The hosted server takes the same credentials as a bearer token: Authorization: Bearer API_KEY:API_SECRET for a signature-based project, or Authorization: Bearer API_KEY for an API Key Only project.

Available Tools

ToolDescription
search_modelsSearch and browse AI models by keyword, category, or owner
get_model_schemaGet full parameter schema and pricing for any model
recommend_modelDescribe what you want to build, get model recommendations by relevance
exploreBrowse curated models grouped by category, no parameters needed
run_modelRun any model, waiting up to 45s by default before it returns a recoverable task token
wait_for_taskContinue waiting for an existing task without submitting or billing a duplicate run
get_taskCheck task status immediately or wait up to 45s with wait_seconds
list_tasksBrowse authenticated task history across conversations, then continue with get_task
get_task_priceGet the cost of a completed task
cancel_taskCancel a queued task
kill_taskKill a running task
upload_fileUpload a file from a public http(s) URL (up to 200 MB) for use as model input
search_docsSearch the Wiro documentation for guides and API references

For long generations, run_model returns the existing task ID and token when its wait budget expires. The assistant must continue with wait_for_task; retrying run_model creates a separate billable task.

LLM-friendly responses

All tools publish typed MCP input and output schemas. Successful calls return structuredContent for reliable chaining, concise text content for clients that only render text, and MCP resource links for generated media. Model parameters remain catalog-driven: json and json-array fields are sent as structured values in the same run_model.params object as all other inputs. Use get_model_schema as the source of truth for continuation fields. previousTaskToken is the single continuation reference. Send it with exactly one new prompt or non-empty messages value for a stateful next turn, or with toolOutputs for a tool-result continuation.

LLM task outputs preserve the public Task Detail segment names and casing: thinking, answer, function_call, and custom_tool_call, including call_id, finishreason, and optional normalized token usage. Only validated fields are projected into structured MCP output. When segments are present, response is derived from ordered answer segments instead of raw debug transport; tasks without a typed projection retain their normal debugoutput response.

Completed tool calls return a continuation template in the existing nextAction. Execute each call, replace the output placeholders, and pass the same ordinary run_model.params object back:

{
  "tool": "run_model",
  "arguments": {
    "model": "owner/model",
    "params": {
      "previousTaskToken": "task-token",
      "toolOutputs": [
        {
          "call_id": "call_01",
          "output": "<tool result>"
        }
      ]
    }
  }
}

Function calls carry JSON-string arguments; custom tool calls carry free-form input. Tool results are request values in toolOutputs, not response segments.

Completed media responses also include an assistant-audience delivery instruction. Some MCP clients expose a resource_link as tool metadata instead of previewing it inside the tool card, so the assistant is explicitly told to render images and preserve clickable media links in its user-facing response. The standard resource link and full-resolution URL remain available to every client; no base64 media payload is required.

Task responses use the stable states submitted, running, completed, failed, and cancelled. When more work is required, the response includes an executable nextAction:

{
  "state": "running",
  "task": {
    "id": "123",
    "token": "task-token",
    "status": "task_start"
  },
  "outputs": [],
  "nextAction": {
    "tool": "wait_for_task",
    "arguments": { "tasktoken": "task-token" },
    "reason": "Continue this exact task. Do not call run_model again."
  }
}

Generation chain: search_models → get_model_schema → run_model → wait_for_task

Cross-conversation history: list_tasks → get_task

Hosted MCP Server

Wiro AI also hosts the same tools at https://mcp.wiro.ai/v1 over streamable HTTP, so nothing has to be installed locally. Send your credentials in the Authorization header as shown under Authentication. The MCP Server documentation has setup instructions for each client.

Install as a plugin

wiroai/Wiro-Plugin packages the hosted server as a plugin for Cursor, Claude Code, Gemini CLI and Devin. Its README has the install command for each of them.

Documentation

Using as a Library

This package exports its core components for use in custom MCP servers:

import { WiroClient } from '@wiro-ai/wiro-mcp/client';
import { createMcpServer } from '@wiro-ai/wiro-mcp/server';

const client = new WiroClient('your-api-key', 'your-api-secret');
const server = createMcpServer(client);

If a project uses signature-based auth and no API secret was given, tool errors say that the secret is missing. When your server takes credentials in its own way, tell users where the secret goes:

const client = new WiroClient(apiKey, apiSecret, undefined, {
  missingSecretHint: 'This project uses signature-based auth. Enter API_KEY:API_SECRET as the API key.',
});
Exports
ExportDescription
createMcpServer(client)Creates an McpServer with all 13 tools registered
WiroClientAPI client with both auth types
registerTools(server, client)Register tools on an existing McpServer
// Import specific components
import { WiroClient } from '@wiro-ai/wiro-mcp/client';
import { registerTools } from '@wiro-ai/wiro-mcp/tools';

Environment Variables

VariableRequiredDescription
WIRO_API_KEYYesYour Wiro project API key
WIRO_API_SECRETNoYour Wiro project API secret (for signature auth)
WIRO_API_BASE_URLNoOverride API base URL (default: https://api.wiro.ai/v1)

More from Wiro AI

RepositoryWhat it is
Wiro-PluginWiro AI plugin for Cursor, Claude Code, Gemini CLI and Devin
Swift-QuickStartWiroKit, the Wiro AI SDK for iOS
Kotlin-QuickStartWiroKit, the Wiro AI SDK for Android
Dart-QuickStartWiro AI SDK for Dart and Flutter, wiro on pub.dev
ReactNative-QuickStartWiro AI SDK for React Native and Expo, @wiro-ai/wiro-react-native on npm
Swift-RealtimeRealtime voice AI example for iOS
Kotlin-RealtimeRealtime voice AI example for Android
Dart-RealtimeRealtime voice AI example for Flutter
ReactNative-RealtimeRealtime voice AI example for React Native
n8n-nodes-wiroaiWiro AI nodes for n8n, @wiro-ai/n8n-nodes-wiroai on npm
Wiro-DocsSource of the Wiro AI API docs

Website · Models · Docs · X

License

MIT, see LICENSE.

评论

支持 Markdown

第一次接触 MCP?

从协议是什么,到在客户端里装上第一个服务,这几条回答覆盖了大多数入门问题。

一个开放协议,规定了 AI 应用如何以统一方式连接外部工具与数据源。客户端负责与模型对话,MCP 服务负责提供工具、资源和提示模板,两者通过标准消息通信,同一个服务可以被不同客户端复用。