Batchit MCP Server

Batch any Python iterator by count and/or elapsed time. Exposed over MCP by the batchit mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.

What it actually does

Batch any Python iterator by count, weight, elapsed time, or any combination — in one pip install, with no dependencies.

• Sync and async — variants with consistent semantics
• Partial final batch — always flushed, never silently dropped
• Timeout measured correctly — from the first item in the batch, not wall clock
• Async timeout fires independently — of item delivery (via asyncio.wait_for) — not just on arrival
• Weight-based flushing — for token budgets, byte limits, or any custom metric
• Queue draining — for producer/consumer patterns with asyncio.Queue

Adding it to your client

batchit on PyPI is all you need. Most clients run it directly, so configuration is a few lines and a restart.

When to reach for it

Plenty of monitoring and observability servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Caveats

• It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
• MCP clients confirm each tool call by default. Leave that on until you have watched what the batchit mcp server does with a few real requests.