TinyRex MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| APIFY_TOKEN | Yes | Your Apify API token, required to run TinyRex actors. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_actorsA | List all public TinyRex Apify Store actors this MCP can run. Returns name, title, short description, Store URL, and an example input for each actor. Private / ToS-blocked actors are not included. |
| run_actorA | Run a TinyRex Apify actor and return dataset items. Args: actor: Actor name (e.g. "gleif-lei-lookup") or "tinyrex/". input: Actor input object (same fields as on the Apify Store). Use list_actors exampleInput as a starting point. max_items: Max dataset items to return (default 50). Total count is always included. timeout_secs: How long to wait for the run to finish (default 180). memory_mbytes: Optional memory override for the run (Apify default if omitted). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: list_actors for discovery and run_actor for execution. There is no overlap, and the descriptions explain their relationship through the exampleInput field.
Both names follow a consistent snake_case verb_noun pattern: list_actors and run_actor. The verbs are distinct and the noun is consistent.
Only two tools are provided, which is below the typical 3-15 range and may feel thin for a server that might need run management. However, for the narrow scope of discovering and running actors, it could be sufficient.
The surface covers actor discovery and execution, including example inputs and result retrieval. However, it lacks operations for managing runs (e.g., status, cancellation, or retrieving past runs), which agents might need for long-running or async actors.