Batchit
Batchit is an open-source MCP server that enables batching of multiple Model Context Protocol (MCP) tool calls into a single request, reducing token usage and network overhead for AI agents.
Features
- Batch Execution: Aggregate multiple MCP tool calls into a single
batch_execute request.
- Parallel Execution: Run multiple operations simultaneously, with configurable concurrency via
maxConcurrent option.
- Error Handling: Option to stop remaining operations if one fails (
stopOnError).
- Timeout Control: Set timeout limits for the entire batch using
timeoutMs.
- Connection Caching: Reuses connections to downstream MCP servers for efficiency.
- Single Target Server Per Batch: Each batch call is directed to one MCP server.
- Consolidated Results: All operation responses are returned together at the end of the batch.
- Installation via Git: Clone and run with TypeScript/Node.js.
- Compatible with Cursor: Can be added globally or per project in Cursor environments.
Limitations
- No data passing between operations within a batch; dependent operations require separate batch calls.
- Each batch references only a single target MCP server.
- All results are returned together at the end of the batch.
Usage Examples
- Reading multiple files in one batch
- Creating directories and writing multiple files based on prior operations (requires phased requests)
Category
mcp-middleware-orchestration
batching, orchestration, ai-agent, open-source
Pricing
No pricing information is provided; Batchit is open-source.
Source
GitHub repository
