Loop MCP Server

An MCP (Model Context Protocol) server that enables LLMs to process arrays item by item with a specific task.

- Initializing an array with a task description
- Fetching items one by one or in batches for processing
- Storing results for each processed item or batch
- Retrieving all results (only after all items are processed)
- Optional result summarization
- Configurable batch size for efficient processing
-

initialize_array- Set up the array and task

- array: The array of items to process
- task: Description of what to do with each item
- batchSize(optional): Number of items to process in each batch (default: 1)

get_next_item- Get the next item to process

- Returns: Current item, index, task, and remaining count

get_next_batch- Get the next batch of items based on batch size

- Returns: Array of items, indices, task, and remaining count

store_result- Store the result of processing

- result: The processing result (single value or array for batch processing)

get_all_results- Get all results after completion

- summarize(optional): Include a summary
- Note: This will error if processing is not complete

reset- Clear the current processing state

// 1. Initialize await callTool('initialize_array', { array: [1, 2, 3, 4, 5], task: 'Square each number' }); // 2. Process each item while (true) { const item = await callTool('get_next_item'); if (item.text === 'All items have been processed.') break; // Process the item (e.g., square it) const result = item.value  item.value; await callTool('store_result', { result }); } // 3. Get final results const results = await callTool('get_all_results', { summarize: true });

// 1. Initialize with batch size await callTool('initialize_array', { array: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], task: 'Double each number', batchSize: 3 }); // 2. Process in batches while (true) { const batch = await callTool('get_next_batch'); if (batch.text === 'All items have been processed.') break; // Process the batch const results = batch.items.map(item => item  2); await callTool('store_result', { result: results }); } // 3. Get final results const results = await callTool('get_all_results', { summarize: true });

Add to your Claude Desktop configuration:

{ "mcpServers": { "loop-processor": { "command": "node", "args": ["/path/to/loop_mcp/server.js"] } } }

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