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actors-mcp-server

Official
by apify

Call Actor MCP tool

call-actor-mcp-tool
Destructive

Invoke a specific tool on an Actor's MCP server and return its result; use it to execute Actor-defined actions with matching arguments.

Instructions

Call one tool on an Actor's MCP server and return its result. fetch-actor-mcp-tool-list lists the Actor's MCP tools and their input schemas. It connects with your Apify API token. Connecting can start a Server Actor run in your account, kept until its idle timeout; a multi-tenant Server Actor charges per event. What the tool itself does depends on the Actor.

Example call: {"actor": "username/name", "tool": "search", "arguments": {"query": "apify"}}

USAGE:

  • Use when the user asks to call a tool on an Actor's MCP server.

USAGE EXAMPLES:

  • user_input: Use the search tool of username/name to look up apify

Input Schema

NameRequiredDescriptionDefault
toolYesThe name of the tool on the Actor's MCP server.
actorYesThe MCP server Actor: its ID, or its name in the "username/name" form.
argumentsNoThe tool's arguments, matching its input schema. Omit for a tool that takes none.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.19.5

TDQS

A3.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the destructive/openWorld/non-idempotent annotations, the description discloses non-obvious side effects: connecting requires an Apify API token, can start a Server Actor run that persists until idle timeout, and a multi-tenant Server Actor charges per event. Failure behavior (nonexistent actor or tool) is not covered, which keeps it from a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core action is front-loaded in sentence one, with cost/persistence caveats in the middle and a compact example at the end. No sentence is pure filler, though the example JSON partially restates the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description only says it returns the target tool's result while noting that behavior "depends on the Actor" — acceptable given the result shape is inherently delegated. The important hidden costs and resource-lifecycle facts are present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already defines actor, tool, and arguments. The description's example call reinforces the "username/name" form and the {tool, arguments} pairing, but adds no semantics the schema lacks about the free-form arguments object.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

First sentence states a specific verb and resource (call one tool on an Actor's MCP server, return its result) and points at fetch-actor-mcp-tool-list as the discovery counterpart. It does not address the adjacent sibling call-actor, so an agent can't fully disambiguate between the two from the description alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Use when the user asks to call a tool on an Actor's MCP server" plus a worked user_input example gives implied context, but there is no when-not guidance and no explicit comparison to call-actor, which is the most plausible alternative for the same intent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.