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MCP server for model discovery, pricing lookup, media task creation, and balance checks.","maintainers":[{"name":"runapi-ai","email":"contact@runapi.ai"}],"readme":"<h1 align=\"center\">RunAPI MCP Server</h1>\n\n<p align=\"center\">\n  <strong>一个 MCP Server，把 160+ 个可执行模型、4 种模态的模型发现、价格查询、媒体任务和账户状态接入 AI 编程工具。</strong>\n</p>\n\n<p align=\"center\">\n  <a href=\"https://www.npmjs.com/package/@runapi.ai/mcp\"><img src=\"https://img.shields.io/npm/v/%40runapi.ai/mcp?style=flat-square&color=blue\" alt=\"npm version\"></a>\n  <a href=\"LICENSE\"><img src=\"https://img.shields.io/badge/License-Apache--2.0-lightgrey?style=flat-square\" alt=\"Apache-2.0 license\"></a>\n  <img src=\"https://img.shields.io/badge/Type-MCP_Server-blue?style=flat-square\" alt=\"MCP Server\">\n</p>\n\n---\n\n## 这是什么？\n\nRunAPI MCP Server 让 Claude Code、Cursor、VS Code、Windsurf、Roo 等 MCP Host 可以直接使用 RunAPI。\n它支持浏览模型目录、查看模型输入参数、查询价格快照、创建媒体任务、轮询任务状态和查询账户余额。\n\n目录发现工具不需要 API Key，因为它们使用包内嵌的构建时目录数据。\n认证工具可以使用 `login` tool、`runapi login`、`RUNAPI_API_KEY` 或共享的 RunAPI config。\n\n---\n\n## Hosted MCP\n\n远程 MCP Client 可以直接连接：\n\n```text\nhttps://mcp.runapi.ai/mcp\n```\n\n无需安装 Node.js。Client 支持远程 MCP 授权时使用 OAuth，也可以把 RunAPI API Key 配置为 bearer credential。Cursor、Claude Desktop、VS Code 和 Windsurf 的配置见 [Hosted MCP 设置页面](https://runapi.ai/mcp)。\n\nHosted MCP 提供下文列出的 8 个 Business Tools。Local Login 只保留在 Local MCP package 中。\n\n---\n\n## 快速开始\n\n通过 stdio 使用 Local MCP 时，推荐使用 Claude Code 的 MCP 命令安装：\n\n```bash\nclaude mcp add runapi -s user -- npx -y @runapi.ai/mcp\n```\n\nscope 参数决定 MCP Server 配置保存在哪里：\n\n- `-s user`：全局配置，对当前用户的所有项目可用。\n- `-s project`：团队共享配置，写入当前仓库的 `.mcp.json`，可以提交到 repo。\n\n如果希望团队共享同一份配置，使用 project scope：\n\n```bash\nclaude mcp add runapi -s project -- npx -y @runapi.ai/mcp\n```\n\n非 Claude Code 平台或手动 JSON 配置的兼容 fallback：\n\n```json\n{\n  \"mcpServers\": {\n    \"runapi\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@runapi.ai/mcp\"]\n    }\n  }\n}\n```\n\n如果你的 MCP Host 需要生成平台专用配置文件，可以把旧的 `init` 命令作为 fallback：\n\n```bash\nnpx @runapi.ai/mcp init claude\nnpx @runapi.ai/mcp init cursor\nnpx @runapi.ai/mcp init vscode\nnpx @runapi.ai/mcp init windsurf\nnpx @runapi.ai/mcp init roo\n```\n\n免费目录工具登录前即可使用。\n创建任务、查询任务和查询余额时，让助手调用 `login` tool。它会打开浏览器登录，并把凭据保存到 `~/.config/runapi/config.json`，也就是 `runapi login` 使用的同一个文件。\n无浏览器或 CI 环境仍然可以在启动 MCP Host 前设置 `RUNAPI_API_KEY`。\n\n---\n\n## 工具\n\n| Tool | 认证 | 用途 |\n|---|---|---|\n| `list_models` | 否 | 从内嵌目录列出 RunAPI 模型，支持 `modality`、`service`、`action` 过滤。 |\n| `get_model_info` | 否 | 返回某个模型 slug 的 service、action、modality、输入约束和价格快照。模型出现在多个 endpoint 时，带上 `service` + `action` 精确查询。 |\n| `list_actions` | 否 | 按 modality 分组列出 endpoint action 名称。 |\n| `check_pricing` | 否 | 查询 `service` + `action` + `model` 组合的价格快照。 |\n| `search_prompts` | 否 | 按 `modality`、`category`、`tags`、`q`、`model`、`featured` 和分页搜索可复用 prompt 示例。 |\n| `login` | 否 | 打开浏览器登录，并把 RunAPI 凭据保存到共享本地配置。 |\n| `create_task` | 是 | 使用调用方生成的必填 `idempotency_key` 创建媒体任务；默认等待完成，也可用 `wait: false` 立即返回。 |\n| `get_task` | 是 | 查询已有媒体任务的状态和最新 payload。 |\n| `check_balance` | 是 | 查询账户余额和消费指标。 |\n\n---\n\n## 示例\n\n你可以用自然语言让助手调用工具。\n助手应该通过工具发现当前模型 slug 和价格，而不是依赖记忆里的模型名。\n\n### 浏览目录\n\n```text\nRunAPI 有哪些图片模型？\n```\n\n预期行为：\n\n1. 调用 `list_models`，传入 `modality: \"image\"`。\n2. 总结返回的 model slug、service、action 和 required fields。\n3. 除非调用 `check_pricing`，否则不直接报价。\n\n### 搜索 Prompt 示例\n\n```text\n找一些 logo 图片 prompt 示例。\n```\n\n预期行为：\n\n1. 调用 `search_prompts`，传入 `modality: \"image\"` 和 `q: \"logo\"`。\n2. 总结返回的 title、prompt text、model slug、category 和 tags。\n3. 创建任务前，先用 `get_model_info` 检查选中模型的参数约束。\n\n### 查看模型参数\n\n```text\n查看这个模型 slug 的必填参数：<model-slug>\n```\n\n预期行为：\n\n1. 调用 `get_model_info`。\n2. 如果返回 ambiguous，从 matches 里选择相关 service/action，并带上 `service` 和 `action` 再调用一次 `get_model_info`。\n3. 展示 required fields、enum、range、条件输入规则、支持的 action 和价格快照。\n4. 如果 slug 不存在，提示先用 `list_models` 选择有效 slug。\n\n### 创建媒体任务\n\n```text\n用 RunAPI 生成一张方形产品图，帮我选合适的图片模型。\n```\n\n预期行为：\n\n1. 调用 `list_models` 选择兼容的图片模型。\n2. 带上选定的 service/action/model 调用 `get_model_info` 验证参数和条件输入规则。\n3. 如果请求昂贵、耗时或批量，先确认。\n4. 为这个逻辑任务生成一个 opaque `idempotency_key`，再调用 `create_task`。\n5. 返回 task ID、status、output URLs 和可用的 cost 字段。\n\n### 等待任务完成\n\nHosted MCP 对异步 `create_task(wait: true)` 使用 request-scoped SSE，最长等待 300 秒。它约每 5 秒轮询一次、约每 15 秒发送一次 SSE heartbeat；只有 MCP 客户端提供 `progressToken` 时才发送标准 `notifications/progress`。terminal JSON-RPC response 会在同一 stream 中返回，随后关闭 stream。\n\nterminal tool result 的 `structuredContent` 与 text content 语义一致，包含 `task_id`、最终 `status`、`completed: true` 和 RunAPI `result`。参数示例见 [`examples/create-task-and-wait.arguments.json`](examples/create-task-and-wait.arguments.json)。\n\n### 只提交不等待\n\n```text\n创建任务，但不要等待完成。\n```\n\n预期行为：\n\n1. 生成一个 opaque `idempotency_key`，再调用 `create_task` 并传入 `wait: false`。\n2. 返回 task ID。\n3. 之后可以用 `get_task` 查询状态。\n\n### 安全重放任务创建\n\n`create_task` 要求 1 到 512 个字符的 opaque `idempotency_key`。每个逻辑任务生成一个新 key，并把它与该任务的 `service`、`action`、`model` 和 `params` 一起保留。\n\n如果连接中断或超时导致创建结果未知，不要自动创建另一个任务。只有在确实需要重试时，才对相同输入复用原 key；对不同输入复用同一个 key 会返回 conflict。不要从 JSON-RPC request ID 或 `X-Client-Request-Id` 推导这个 key。\n\nCompletion Wait 达到 deadline 时，task 创建仍然成功。这个非错误结果会在 structured 与 text content 中一致返回 `task_id`、最新 `status`、`completed: false`、`wait_deadline_reached: true` 和 `next_action: \"get_task\"`。继续使用 `get_task` 查询，不要创建替代 task。\n\n如果 task 创建后 polling 失败或连接中断，task 仍可能继续处理。继续使用 `get_task` 查询，不要创建替代 task。\n\n只提交不等待的参数结构见 [`examples/create-task.arguments.json`](examples/create-task.arguments.json)。\n\n### 查询余额\n\n```text\n查询我的 RunAPI 余额。\n```\n\n预期行为：\n\n1. 调用 `check_balance`。\n2. 如果没有配置 key，调用 `login` 进行浏览器登录；无浏览器环境则说明如何设置 `RUNAPI_API_KEY`。\n\n## Catalog Coverage\n\nMCP Embedded Catalog 来自 RunAPI 的 contract 快照。\n它只包含当前 server 版本可执行的模型，共 160+ 个模型、4 种模态。\n\n| Modality | 使用方式 |\n|---|---|\n| Image | `list_models` with `modality: \"image\"` |\n| Video | `list_models` with `modality: \"video\"` |\n| Audio and music | `list_models` with `modality: \"audio\"` |\n| Utility | `list_models` with `modality: \"utility\"` |\n\n目录内容会随着版本变化。\n请用 `list_models` 获取当前 service/action/model slugs，用 `get_model_info` 查看当前约束。\n\n---\n\n## Pricing\n\n价格通过 `check_pricing` 工具和公开 pricing 页面查询。\n不要依赖 README 示例里的固定数字。\n\n推荐流程：\n\n1. 调用 `list_models` 找候选模型。\n2. 调用 `check_pricing`，传入 `service`、`action` 和 `model`。\n3. 展示返回的价格快照，或链接到 [runapi.ai/pricing](https://runapi.ai/pricing)。\n\n免费目录工具不会创建任务，也不会消耗余额。\n\n---\n\n## 平台配置\n\n### Claude Code、Cursor、Windsurf 和 VS Code\n\n运行：\n\n```bash\nclaude mcp add runapi -s user -- npx -y @runapi.ai/mcp\n```\n\n`-s user` 表示全局安装，对所有项目可用。\n`-s project` 表示让 Claude Code 在仓库里写入 `.mcp.json`，用于团队共享配置。\n\n修改 MCP 配置后，重启或重新加载你的 MCP Host。\n\n### 兼容 Fallback：生成配置文件\n\n只有当 Host 需要平台专用 JSON 文件，或无法使用 Claude Code MCP 命令时，才使用 `init`。\n\nClaude Code fallback：\n\n```bash\nnpx @runapi.ai/mcp init claude\n```\n\n会在当前目录写入 `.mcp.json`。\n\nCursor fallback：\n\n```bash\nnpx @runapi.ai/mcp init cursor\n```\n\n会写入 `.cursor/mcp.json`。\n\nVS Code fallback：\n\n```bash\nnpx @runapi.ai/mcp init vscode\n```\n\n会写入 `.vscode/mcp.json`。\nVS Code 生成配置使用顶层 `servers` 和 `type: \"stdio\"`。\n\nWindsurf fallback：\n\n```bash\nnpx @runapi.ai/mcp init windsurf\n```\n\n### Roo Code\n\n```bash\nnpx @runapi.ai/mcp init roo\n```\n\n会写入 `.roo/mcp.json`。\n\n---\n\n## 配置\n\nServer 按以下顺序读取配置：\n\n1. `RUNAPI_API_KEY` 环境变量，适合无浏览器和 CI 环境\n2. `~/.config/runapi/config.json`，由 MCP `login` tool 或 `runapi login` 创建\n3. 无 key，仅允许免费目录工具\n\n配置文件通常由登录流程管理。无浏览器环境预置配置时可以使用：\n\n```json\n{\n  \"apiKey\": \"your_runapi_key\"\n}\n```\n\n不要提交真实 API Key。\n\n---\n\n## Data Sync\n\n包内包含构建时数据：\n\n- `data/contract.json`：目录、action、model slug 和输入约束\n\n发布前刷新 contract 数据：\n\n```bash\nnpm run sync:data\n```\n\n---\n\n## 开发\n\n```bash\nnpm install\nnpm run typecheck\nnpm test\nnpm pack --dry-run\n```\n\n本地启动：\n\n```bash\nnpm run dev\n```\n\n---\n\n## Package Contents\n\nnpm 包包含：\n\n- 编译后的 `dist/`\n- 内嵌 `data/`\n- 平台示例\n- eval scenarios\n- README、CHANGELOG、LICENSE、package metadata\n\n不包含 `node_modules`、`.env`、本地配置文件或 API Key。\n\n---\n\n## License\n\nLicensed under the [Apache License, Version 2.0](LICENSE).\n","readmeFilename":"README.zh-CN.md"}