@gcszhn/mcp-sentinel-deepseek-harness-plugin
A DeepSeek Harness plugin
that acts as a sentinel between the AI agent and MCP servers — polling
long-running tasks on the agent's behalf so that token-costly status loops never
enter the LLM inference path.
This package is the DeepSeek Harness adapter for @gcszhn/mcp-sentinel-core.
Install
Install into a profile with the dsh CLI:
dsh plugin --profile <name> add @gcszhn/mcp-sentinel-deepseek-harness-plugin
The package ships a dsh.bundle manifest, so dsh plugin add appends it to the
profile's dsh.profile.bundles list and activates its cordis.patch.yml layer.
Verify the layer without booting:
dsh --profile <name> --dump-config
How it talks to MCP
The plugin runs in external-invoker mode: it reuses the MCP tools already
registered by the harness's @deepseek-ai/dsh-mcp-client bridge and never owns
MCP connections itself, so there is no separate servers config and no
sentinel-specific MCP wiring. You keep configuring MCP exactly as you already do
for the harness — one dsh-mcp-client instance per server:
# This is ordinary dsh-mcp-client config, not sentinel config.
- insert:
- id: mcp-ci
name: "@deepseek-ai/dsh-mcp-client"
config:
serverName: ci
transport: stdio
command: bun
args: ["/path/to/ci-mcp-server.ts"]
When calling mcp_sentinel_poll, server is the mcp-client serverName and
tool is the server's raw tool name; the sentinel invokes
mcp__<server>__<tool> (e.g. mcp__ci__get_status) through the harness tool
registry. Anything you already bridged with dsh-mcp-client is immediately
pollable — no extra step.
Tools
mcp_sentinel_poll
Submit a long-running MCP tool call and poll it at regular intervals until a
condition is met. Returns a sentinel ID immediately; when the sentinel
resolves, the plugin pushes a completion notice into the originating agent's
inbox (Agent.followup) so the driver wakes and the agent can collect the
result with mcp_sentinel_attach (blocking), mcp_sentinel_status, or
mcp_sentinel_read.
| Parameter | Type | Default | Description |
|---|
server | string | required | serverName of a dsh-mcp-client instance |
tool | string | required | Tool name to call on the server |
args | object | {} | JSON object of arguments for the tool |
interval | number | 5000 | Poll interval in milliseconds |
timeout | number | optional | Max poll duration in ms (unset = no limit) |
until | object | required | JSON condition object |
mcp_sentinel_status
Check status, list active tasks, or cancel a running task (action =
status | list | cancel).
mcp_sentinel_attach
Block the agent, waiting for a sentinel to complete. Zero token cost during the
wait.
mcp_sentinel_read
Read raw poll outputs with offset/limit pagination.
Condition model
Conditions are pure declarative data:
{ "path": "status", "is": "eq", "value": "completed" } // path leaf
{ "is": "eq", "value": "completed" } // no path: compare the raw result
{ "path": "tasks[0].exit_code", "is": "ne", "value": 0 } // array-index path
{ "not": { "path": "status", "is": "eq", "value": "error" } } // negation
{ "and": [ /* conditions */ ] } // logical AND
{ "or": [ /* conditions */ ] } // logical OR
Operators: eq, ne, gt, gte, lt, lte, contains, match.
Omit path (or leave it empty) to match a non-JSON tool result directly.
License
MIT
