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Documentation Index

Fetch the complete documentation index at: https://apixo.ai/docs/llms.txt

Use this file to discover all available pages before exploring further.

APIXO MCP is a local Model Context Protocol server that plugs APIXO into any MCP-compatible AI client. It exposes APIXO’s full model catalog and per-model parameter schemas to your agent, so when you ask “add APIXO to my project”, the agent can write correct integration code — without you reading docs or guessing field names. It works in any client that speaks MCP. Common ones:
  • Cursor (config file: ~/.cursor/mcp.json)
  • Claude Code (CLI: claude mcp add ...)
  • Codex CLI (CLI: codex mcp add ...)
  • Claude Desktop, Windsurf, Cline, Continue, Zed, and other MCP clients (any client that loads stdio MCP servers from JSON config)
The server ships as the @apixo/mcp-server npm package and runs locally on your machine. It authenticates with your APIXO API key and talks to the same endpoints documented under Generation APIs and the LLM Gateway.

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What you can do

Scaffold APIXO into your codebase

Ask your agent to add a model to your project. It reads the model schema through MCP and writes parameter-accurate calls into your existing files.

Discover models and schemas

Your agent can browse APIXO’s model catalog and fetch any model’s full input schema on demand — no copy-pasting from the docs.

Run and inspect tasks from chat

The same tools also let the agent submit ad-hoc generation tasks and check your account balance directly from the conversation.
Most of the value is in the first capability: APIXO has many models with very different input parameters, and MCP gives the agent a reliable source of truth so the code it writes against APIXO compiles and runs on the first try.

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Tools exposed by the server

@apixo/mcp-server registers the following tools. Most clients show them under an “apixo” namespace.
ToolWhat it does
apixo_list_modelsList APIXO models from the published schema index. Supports filtering by category (image, video, audio, text) and integration_type (task_api, llm_gateway).
apixo_get_model_schemaFetch one model’s full schema by model_id or slug, including all input parameters.
apixo_generate_taskSubmit a generation task to POST /api/v1/generateTask/{model} with model-specific input. Supports async and callback request types.
apixo_get_task_statusFetch a task’s status and result from GET /api/v1/statusTask/{model}?taskId=....
apixo_get_balanceRead the current balance for the API key the server is configured with.
Together, apixo_list_models + apixo_get_model_schema + apixo_generate_task + apixo_get_task_status cover the full Generation task flow described in How APIXO Works.

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When to use MCP

Use MCP when…You probably don’t need MCP when…
You’re integrating APIXO into a project with an AI coding tool openYour integration is already shipped and stable on the REST APIs
You’re evaluating multiple models and want the agent to write the glue code for eachYou only call APIXO from a backend service that humans maintain
You want a chat-driven way to submit tasks or check account state while developingYou only use APIXO’s LLM Gateway — point your existing Claude / OpenAI / Gemini SDK at the gateway base URL instead

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Get started

Install APIXO MCP

Step-by-step setup for Cursor, Claude Code, Codex, and other MCP clients on Windows, macOS, and Linux.

Troubleshooting

Fix common issues: codex not on PATH, API key not picked up, npx failures, missing tools in the client.