OpenCode plugin that acts as a sentinel between the AI agent and MCP servers — polling long-running tasks so token-costly status loops never enter the LLM inference path
View on GitHub ↗A plugin for OpenCode 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.
When an agent submits a long-running job through an MCP tool, it must repeatedly call the server to check progress — each round-trip burns context window tokens.
opencode-mcp-sentinel moves the polling loop out of the agent and into the plugin runtime — 2 inference calls regardless of task duration.
Add to your opencode.jsonc (project-level .opencode/opencode.jsonc or global ~/.config/opencode/opencode.jsonc):
The plugin reads your existing MCP server configs — no additional setup needed.
Environment variables for controlling memory usage:
Variable Default Description ----------------------- --------- ------------------------------------------------- SENTINELMAXPOLLLOG unlimited Max poll log entries per task (FIFO trim) SENTINELTASKTTLMS unlimited Auto-cleanup completed tasks after N milliseconds
Both accept positive integers only. Zero, negative, or non-numeric values are treated as unlimited/disabled.
Submit a long-running MCP tool call and poll it at regular intervals until a condition is met. The sentinel polls silently (zero token cost) and notifies you when done.
Parameter Type Default Description ---------- ------ ---------- ------------------------------------------ server string required MCP server name (from opencode config) tool string required Tool name to call on the server args string "{}" JSON string of arguments for the tool interval number 5000 Pol
From the project README.
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