ryanjoachim/mcp-batchit
🚀 MCP aggregator for batching multiple tool calls into a single request. Reduces overhead, saves tokens, and simplifies complex operations in AI agent workflows.
This project helps AI agents or large language models (LLMs) perform multiple tasks on a server, like reading or writing files, in a single request. Instead of making many separate calls, you can send one 'batch_execute' request with a list of operations, reducing communication overhead and saving on token usage. It's designed for developers building or managing AI agents that interact with Model Context Protocol (MCP) servers.
No commits in the last 6 months.
Use this if your AI agent or LLM frequently performs several independent operations on an MCP server (e.g., a filesystem server) and you want to reduce latency and token costs by consolidating them into one request.
Not ideal if your AI agent's operations are highly sequential, where the output of one step is immediately needed as input for the next, as this tool does not support data passing between operations within a single batch.
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JavaScript
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Last pushed
Mar 14, 2025
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