What is the APIXO AI remote MCP server?

The APIXO AI remote MCP server is a hosted Model Context Protocol endpoint at https://mcp.apixo.ai/mcp, so AI assistants can connect to it without installing or running anything locally.

How do I connect to the APIXO AI MCP server?

Add the endpoint https://mcp.apixo.ai/mcp to any MCP-compatible client such as Claude Code, Cursor, or VS Code. The setup snippets on this page configure each client in one step.

Does the APIXO AI MCP server require authentication?

Authentication requirements for APIXO AI have not been confirmed in this listing. Check the provider’s documentation before connecting.

Which transport does the APIXO AI MCP server use?

APIXO AI exposes a Streamable HTTP endpoint, the transport used by remote MCP servers and supported by all major MCP clients.

APIXO AI MCP Server: Tools, Setup & Config

Read the current public task_api index and its default tool-to-model bindings. No model defaults are built into the plugin. LLM gateways are excluded. Modes and attachment_fields/result_codec load on schema lookup. Candidate eligibility does not prove successful real generation. Free public discovery; unavailable upstream returns an error.

Read the complete published task model schema by canonical ID or exact slug. The schema field preserves all descriptions, examples, nested structures, constraints and AI guidance without filtering or normalization. APiXO uses custom request_schema.input.properties arrays, not standard JSON Schema. Follow schema for model parameters; the backend validates them. execution only describes transport/result adaptation and explicit attachment fields, not field or mode permissions. Result codecs and attachment paths come from schema.mcp, never model ID eligibility lists. New result formats require a supported decoder. Free, no account needed.

Read prices for the connected APIXO account. Pass a canonical public model ID, or omit model to read all published, currently available models, including LLM prices. Returns specifications, base and final unit prices, billing units and the applied discount type. Read-only and free; any valid MCP login is sufficient. Prices are reference unit rates, not a generation quote. A task-model fixed unit price already includes the applicable account pricing; never apply a discount again. LLM rates follow the applicable token-billing discounts. PER_1M_TOKENS means per million tokens. Some models have multiple billable components or quantity limits; preserve the specification and billing unit. Pricing does not establish that this plugin can generate with a model; use list_models/get_model_schema for execution support.

Return the APIXO profile connected to this OAuth session. Normally summarize the connected account using its display name; include its email only when relevant to the user's request. Do not print the profile ID by default. In user-facing replies, omit technical identifiers by default, including user/profile IDs, task_id, session_id, run_id, base_run_id, voice_id, and file IDs. Retain the exact returned identifiers for tool arguments, task queries, session continuation, version appends, and voice reuse; never redact, regenerate, or guess these references. Show an identifier only when the user explicitly asks for it or a specific troubleshooting step requires that exact value, and show only the reference needed. Prefer plain-language status, model names, result previews/download links, and Studio links built from the returned session_id. This changes reply presentation only; tool result fields remain available for the workflow.

Create one independent billable Studio task. All creation tools use input with original model parameters, reference_files and explicit file_bindings. Read list_models.defaults for the default model of this tool, then get_model_schema for the complete schema. generate_task requires model; shortcuts may omit it. Explicit model selects that public task model. Set the documented mode in input; no mode, model fields, defaults or voice choices are inferred or injected. Flat model parameters and legacy reference_images/reference_audio are not accepted. Backend validation is authoritative. Use session_title for a new topic, session_id to continue, and session_id plus base_run_id for a version. Preserve returned model/task_id/session_id/run_id/media_type. Never automatically resubmit or change model/session after rejection or an unconfirmed submission. In user-facing replies, omit technical identifiers by default, including user/profile IDs, task_id, session_id, run_id, base_run_id, voice_id, and file IDs. Retain the exact returned identifiers for tool arguments, task queries, session continuation, version appends, and voice reuse; never redact, regenerate, or guess these references. Show an identifier only when the user explicitly asks for it or a specific troubleshooting step requires that exact value, and show only the reference needed. Prefer plain-language status, model names, result previews/download links, and Studio links built from the returned session_id. This changes reply presentation only; tool result fields remain available for the workflow.

Get task status and results using the supplied model and task_id. task_id is the public APiXO ID; a valid connected identity may query a known task from another account or chat. For a schema declaring mode_media_types automatically carry speech/voice media_type from creation. It is needed when lifecycle fields are absent. Do not guess from task IDs or URLs. Read-only queries may retry finitely. Missing tasks, unavailable models, or query errors must not trigger model switching or generation resubmission. Missing session/Run references, progress, and completion times are not inferred. In user-facing replies, omit technical identifiers by default, including user/profile IDs, task_id, session_id, run_id, base_run_id, voice_id, and file IDs. Retain the exact returned identifiers for tool arguments, task queries, session continuation, version appends, and voice reuse; never redact, regenerate, or guess these references. Show an identifier only when the user explicitly asks for it or a specific troubleshooting step requires that exact value, and show only the reference needed. Prefer plain-language status, model names, result previews/download links, and Studio links built from the returned session_id. This changes reply presentation only; tool result fields remain available for the workflow.

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