Developer · Local MCP server
mdflow — Context OS for AI Coding Agents
Context OS for AI coding agents: task-scoped AST context, verified mutation, and rollback.
What the MCP Registry states
The entry as published to the official MCP Registry (read 2026-10-04), latest version.
- Registry name
io.github.yubinbin32-ops/mdflow- Version
- 0.3.7
- Status
- Active
- Category
- developer
- Transport
- stdio (local process)
- Package
- OCI image (Docker)
- Published
- 2026-09-11
- Updated
- 2026-09-11
- Publisher
- yubinbin32-ops (GitHub)
- Repository
- github.com/yubinbin32-ops/Mdflow-Canvas
- Source
- Registry API entry
Packages
| Registry | Package | Version | Transport |
|---|---|---|---|
| OCI image (Docker) | ghcr.io/yubinbin32-ops/mdflow:0.3.7 | — | stdio |
How to connect mdflow — Context OS for AI Coding Agents
mdflow — Context OS for AI Coding Agents runs locally from a container image in an OCI registry such as Docker Hub or GitHub Container Registry: ghcr.io/yubinbin32-ops/mdflow:0.3.7. It speaks MCP over stdio, so the client starts it as a program and talks to it through standard input and output. It needs Docker or another OCI container runtime; started with docker run — the usual command is docker run -i --rm -e MDFLOW_PROJECT_ROOT ghcr.io/yubinbin32-ops/mdflow:0.3.7. It reads the environment variable MDFLOW_PROJECT_ROOT; set it in the client's configuration for this server.
In the mcpServers JSON format that many desktop and editor MCP clients read, the entry looks like this (placeholders in angle brackets):
{
"mcpServers": {
"mdflow": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MDFLOW_PROJECT_ROOT",
"ghcr.io/yubinbin32-ops/mdflow:0.3.7"
],
"env": {
"MDFLOW_PROJECT_ROOT": "<value>"
}
}
}
}Derived from the registry entry, not tested here. What the server does, and on what terms, is set by its publisher; check its repository or website before giving it access to your accounts or files. How to add an MCP server to an assistant · Before you connect
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