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Dagpipe

devilsfave/dagpipe

If you've ever watched an LLM pipeline crash three hours in and had to start over from scratch, this is the fix. DagPipe exposes operations for building multi-step AI workflows with automatic checkpoint recovery, where each node's output is validated and saved before moving forward. A failure at step 4 doesn't erase steps 1 through 3. Just rerun and it picks up where it stopped. The server integrates a model router that sends simple tasks to free-tier models and escalates complex ones, plus semantic assertions that catch structurally valid but logically wrong output. It's built for stdio transport and works with any MCP-compatible client. The checkpointing is filesystem-based by default, no database required, and the whole thing runs on free API tiers.

GitHub stars
3
tool
1
transport
STDIO
last updated
Mar 15, 2026
View on GitHub

Tools

1 tools

Public tool metadata for what this MCP can expose to an agent.

generate_pipelineGenerate a complete crash-proof DagPipe workflow from plain English.1 params

Generate a complete crash-proof DagPipe workflow from plain English.

Parameters* required
descriptionstring

Sponsors

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Readme

api
DagPipe Logo

DagPipe

Typing SVG

View the full README on GitHub

Details

Repository
github.com/devilsfave/dagpipe
Categories
Databases, AI & LLM Tools
Package
dagpipe-core
Transport
STDIO
Registry
MCP registry, active

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