Luisarg03/dsh-memory-vault#memory-mcp

Cordis bundle that connects DeepSeek Harness (DSH) to a persistent OKF memory vault over the Model Context Protocol.

It mounts @deepseek-ai/dsh-mcp-client configured for the vault's Python MCP server (memory-vault-server in this repository) over stdio, exposing the vault's tools (search_memory, store_*, export_memories, get_profile, ping) to the agent.

Install

dsh plugin --profile web add @luisarg/memory-mcp

uv on PATH is recommended but not required: the bundled launcher.mjs runs the server with uv run when uv is present and falls back to a pip-managed venv (python3 -m venv + pip install -r requirements.txt, network on first boot) when it is not.

Skills

The package also ships the two skills that drive its tools, so installing it is enough to get the commands — nothing has to be copied into a skill directory:

They register at DSH's bundled rank (600), the weakest in the local discovery table, so a skill of the same name in a user or project root still wins. Each SKILL.md is the single source of its own name, description and usage guidance: the provider parses its frontmatter with yaml, so the same file also works copied into ~/.agents/skills. Registration goes through ctx.inject(['skills'], …), so a deployment with no skill catalog still gets the vault bootstrap and the MCP client.

Configuration

The bundle ships no cwd-dependent paths: the cordis.patch.yml layer resolves both values from the environment. The vault falls back to the OS home (~/.memories, which DSH_HOME does not move); the server to the harness home ($DSH_HOME, or ~/.dsh) — DSH does not chdir, so launching from any directory works.

Development

pnpm install
pnpm build
pnpm test

The bundle manifest (dsh.bundle) makes this package installable through the standard dsh plugin add flow; the patch layer lives in cordis.patch.yml.