mcp server
TrainTools
Recommend paper-backed diagnostics for PyTorch and Hugging Face training problems.
Description as published by the maintainer. Source
- version 0.6.2
- active
active — Most recent push to the repository was 2026-07-22.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 0 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-07-22 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 1 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 0.6.2 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-16 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-07-16 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub |
Where to get it
Related, by what their authors tagged them
-
io.github.habedi/omni-lpr
— last commit 2026-07-05, shares deep-learning, mlops
An MCP server for automatic license plate recognition
-
ChatSpatial
— last commit 2026-08-03, shares machine-learning, pytorch
Natural language-driven spatial transcriptomics analysis with 60+ methods via MCP
-
com.secdim/mcp
— last commit 2026-07-20, shares training
Personalised developer security learning pathways from SecDim's challenges and courses.
-
io.github.AlvisoOculus/optionsahoy-mcp
— last commit 2026-08-06, shares optimization
Equity comp tax/trade optimizer: ISO/AMT exercise, NSO, RSU, QSBS, concentration, hedging. 50-state.
-
io.github.caelum29/calibre-mcp
— last commit 2026-08-03, shares huggingface
Calibre ebook library server: search, read content, curate metadata, semantic search, gated writes.
-
Islam West Africa Collection (IWAC)
— last commit 2026-08-07, shares huggingface
Read-only access to the Islam West Africa Collection via Hugging Face datasets.
-
Model Ledger
— last commit 2026-07-25, shares mlops
Model inventory and governance: trace deployed models and their dependencies as an append-only log
-
io.github.CogitatorTech/omni-nli
— last commit 2026-02-23, shares mlops
An MCP server for natural language inference
-
io.github.frozo-ai/edgegate-mcp
— last commit 2026-08-05, shares mlops
Regression-test AI models on real Snapdragon and Jetson hardware, with signed evidence for CI.
-
ai.mcpanalytics/analytics
— last commit 2026-08-02, shares machine-learning
The statistical analyst in your AI chat — validated, citable, re-runnable analysis of your data.
These share tags the maintainers applied themselves, such as deep-learning, mlops, machine-learning, pytorch. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: ai-agents, data-quality, deep-learning, early-stopping, gradient-debugging, gradient-noise-scale, huggingface, label-noise, machine-learning, mcp, mlops, optimization, pytorch, training, training-debugging, training-diagnostics.
This record as data
Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.
GET /api/v1/entries/mcp_server.json