mcp-batchit

Overview

MCP BatchIt is an aggregator server in the Model Context Protocol ecosystem that exposes a single 'batch_execute' tool. It allows AI agents to batch multiple MCP tool calls together in one request, rather than making separate calls for each operation. This dramatically reduces token usage, network overhead, and repeated context in conversations. The server handles parallel execution up to a specified concurrency limit, with options for timeout and error handling. While functional, it's actively being developed to address compatibility and transport complexities.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

• batch_execute

  Batch multiple MCP tool calls into a single request for reduced overhead and token usage.

  Try:Execute these file operations in batch: read package.json, read README.md, and create a memory-bank directoryTry:Batch these filesystem operations: create directory, write multiple documentation files, and check if directory existsTry:Run these operations in parallel: read file A, read file B, and write file C

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Installation

git clone https://github.com/ryanjoachim/mcp-batchit.git
cd mcp-batchit
npm install
npm run build
npm start

{
  "mcpServers": {
    "batchit": {
      "command": "node",
      "args": ["/path/to/mcp-batchit/dist/index.js"]
    }
  }
}

FAQ

Can sub-operations pass data between each other in the same batch request?

No. BatchIt doesn't support data passing between sub-operations within the same request. You need to make multiple aggregator calls for dependent operations.

What happens if one sub-operation fails?

If stopOnError is true, the aggregator will halt new sub-ops but continue running already-started ones. Partial results are returned with the failing operation marked appropriately.

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