Loop MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| initialize_arrayC | Initialize the array and task to be processed |
| get_next_itemC | Get the next item to process along with the task |
| get_next_batchB | Get the next batch of items to process based on the configured batch size |
| store_resultC | Store the result of processing the current item or batch of items |
| get_all_resultsB | Get all results after all items have been processed. This tool will return an error if processing is not complete. |
| resetC | Reset the processing state |
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 6 tools
Each tool has a clearly distinct purpose with no overlap: initialize_array sets up processing, get_next_item and get_next_batch retrieve work, store_result saves outcomes, get_all_results aggregates final results, and reset clears state. The descriptions make it unambiguous when to use each tool.
All tools follow a consistent verb_noun naming pattern (e.g., get_all_results, store_result, initialize_array). The naming is uniform and predictable, using snake_case throughout with clear action-object pairs.
With 6 tools, this server is well-scoped for processing tasks, covering initialization, retrieval, storage, aggregation, and reset. Each tool earns its place without redundancy, fitting a typical workflow efficiently.
The toolset provides complete coverage for a processing loop domain: initialize, retrieve items/batches, store results, get final results, and reset. There are no obvious gaps, enabling agents to handle the full lifecycle without dead ends.