Runapi MCP

RunAPI MCP Server

AI image generation, video generation, music creation, text-to-speech, prompt search, and model discovery — 160+ executable models across 4 modalities in one MCP server.

Works with Claude Code, Codex, Cursor, Windsurf, VS Code, Roo Code, and any MCP-compatible host.

Quick Start | Tools | Examples | Catalog | Platforms

What Is This?

RunAPI MCP Server connects MCP-compatible coding tools to RunAPI. It lets an assistant browse the RunAPI catalog, inspect model inputs, check current runtime pricing, create media tasks, poll task status, and check account balance.

The discovery tools work without an API key because they use the embedded build-time catalog. Authenticated operations use the login tool, runapi login, RUNAPI_API_KEY, or shared RunAPI config.

This package is a pure client. It does not run a local generation backend and only needs RunAPI sign-in for authenticated tools.

Hosted MCP

Remote MCP clients can connect directly to:

https://mcp.runapi.ai/mcp

No Node.js installation is required. Use OAuth when the client supports remote MCP authorization, or configure a RunAPI API key as the bearer credential. See the Hosted MCP setup page for Cursor, Claude Desktop, VS Code, and Windsurf configurations.

Hosted MCP exposes the eight Business Tools documented below. Local Login remains available only in the Local MCP package.

Quick Start

For Local MCP over stdio, install RunAPI with Claude Code's MCP command:

claude mcp add runapi -s user -- npx -y @runapi.ai/mcp

The scope flag controls where the MCP server is stored:

• -s user: global, available in all projects for your user.
• -s project: team-shared, written to .mcp.json in the current repo so it can be committed.

Use project scope when you want the whole team to share the same server config:

claude mcp add runapi -s project -- npx -y @runapi.ai/mcp

Compatibility fallback for non-Claude Code platforms or manual JSON config:

{

"mcpServers": { "runapi": { "command": "npx", "args": ["-y", "@runapi.ai/mcp"] } } }

If your host needs a generated config file, use the legacy init command as a fallback:

npx @runapi.ai/mcp init claude

npx @runapi.ai/mcp init cursor npx @runapi.ai/mcp init vscode npx @runapi.ai/mcp init windsurf npx @runapi.ai/mcp init roo

Free catalog tools work before sign-in. For task creation, task status, and balance checks, ask your assistant to call the login tool. It opens a browser login and saves credentials to ~/.config/runapi/config.json, the same file used by runapi login. Headless and CI hosts can still set RUNAPI_API_KEY before starting the MCP host.

Tools

The catalog, pricing, and prompt search tools are designed for funnel-top discovery inside coding tools. The task and balance tools are designed for authenticated workflows.

Examples

Ask your assistant natural-language questions. The assistant should use the tools to discover current model slugs and pricing instead of relying on memorized names.

Browse The Catalog

What RunAPI image models are available?

Expected behavior:

1. The assistant calls list_models with modality: "image".
2. It summarizes the returned model slugs, services, actions, and required fields.
3. It avoids quoting stale prices unless it calls check_pricing.

Search Prompt Examples

Find image prompt examples for a logo.

Expected behavior:

1. The assistant calls search_prompts with modality: "image" and q: "logo".
2. It summarizes returned titles, prompt text, model slugs, categories, tags, and example image URLs.
3. It uses the selected prompt with get_model_info before creating a task.

Inspect A Model

Show me the required parameters for this model slug: <model-slug>

Expected behavior:

1. The assistant calls get_model_info.
2. If the response is ambiguous, it chooses the relevant service/action from the returned matches and calls get_model_info again with service and action.
3. It shows required fields, enum constraints, range constraints, conditional input rules, supported action, and current runtime pricing if available.
4. It tells you to choose another slug with list_models if the slug is not found.

Create A Media Task

Generate a square product image with RunAPI. Pick a suitable image model.

Expected behavior:

1. The assistant calls list_models to choose a compatible image model.
2. It calls get_model_info with the selected service/action/model to read the parameter descriptions.
3. It asks for confirmation if the request is expensive, long-running, or a batch.
4. It generates one opaque idempotency_key for this logical task and calls create_task.
5. It returns task ID, status, output URLs, and cost fields when available.

Wait For Completion

Hosted MCP keeps an asynchronous create_task call with wait: true open as request-scoped SSE for up to 300 seconds. It polls about every 5 seconds, sends an SSE heartbeat about every 15 seconds, and sends standard notifications/progress only when the MCP client supplied a progressToken. The terminal JSON-RPC response arrives in that same stream and then closes it.

The terminal tool result includes matching structuredContent and text content with task_id, final status, completed: true, and the RunAPI result. See examples/create-task-and-wait.arguments.json.

Submit Without Waiting

Create the task but do not wait for completion.

Expected behavior:

1. The assistant generates one opaque idempotency_key and calls create_task with wait: false.
2. It returns the task ID.
3. You can later ask for status with get_task.

Replay A Task Creation Safely

create_task requires an opaque idempotency_key from 1 to 512 characters. Generate one new key for each logical task and retain it with the exact service, action, model, and params used for that task.

If the create result is unknown because the connection closed or timed out, do not automatically create another task. Retry only when intended, using the same key with the same input. Reusing the key with different input returns a conflict. Do not derive the key from a JSON-RPC request ID or X-Client-Request-Id.

When Completion Wait reaches its deadline, task creation remains successful. The non-error result has matching structured and text content with task_id, latest status, completed: false, wait_deadline_reached: true, and next_action: "get_task". Continue with get_task; do not create a replacement task.

If polling fails or the connection closes after task creation, the task may still be processing. Continue with get_task; do not create a replacement task.

See examples/create-task.arguments.json for submit-only arguments.

Check Account Balance

Check my RunAPI balance.

Expected behavior:

1. The assistant calls check_balance.
2. If no key is configured, it calls login for browser login, or explains RUNAPI_API_KEY for headless hosts.

Catalog Coverage

The MCP Embedded Catalog is generated from RunAPI's contract snapshot. It includes only models executable by this server release.

Catalog contents can change between releases. Use list_models for current service/action/model slugs and get_model_info for each model's current constraints.

Pricing

MiniMax H3 pricing

RunAPI pricing is exposed through the check_pricing tool and the public pricing page. Do not rely on examples in README files for exact prices.

Useful flows:

1. Call list_models to find a candidate model.
2. Call check_pricing with service, action, and model.
3. Show the returned current price or link to runapi.ai/pricing.

Free catalog tools do not create tasks and do not consume account balance.

Platform Setup

Claude Code, Cursor, Windsurf, And VS Code

Run:

claude mcp add runapi -s user -- npx -y @runapi.ai/mcp

Use -s user for a global install available in all projects. Use -s project when you want Claude Code to write .mcp.json in the repo for team-shared config.

Restart or reload your MCP host after changing MCP configuration.

Compatibility Fallback: Generated Config

Use init only when a host needs a platform-specific JSON file or cannot use the Claude Code MCP command.

Claude Code fallback:

npx @runapi.ai/mcp init claude

This writes .mcp.json in the current directory.

Cursor fallback:

npx @runapi.ai/mcp init cursor

This writes .cursor/mcp.json. Open Cursor settings to verify the MCP server is enabled.

VS Code fallback:

npx @runapi.ai/mcp init vscode

This writes .vscode/mcp.json. VS Code uses a top-level servers key and type: "stdio" in generated config.

Windsurf fallback:

npx @runapi.ai/mcp init windsurf

This writes the generated config for the Windsurf target used by the init command.

Roo Code

Run:

npx @runapi.ai/mcp init roo

This writes .roo/mcp.json.

Manual Configuration

Use the example files in examples/ as starting points. Each platform has slightly different wrapper keys and file paths, but all run the same command:

npx -y @runapi.ai/mcp

Configuration

The server reads configuration in this order:

1. RUNAPI_API_KEY environment variable, useful for headless and CI hosts
2. `~/.config