refresh_context
[SUPPORT] Single-call post-compaction recovery for planning chats. Returns a COMPACT snapshot — current sprint + progress, next pending items, the active session id, recent handoffs, high-priority (urgent) decisions, unvalidated assumptions, and key note slugs — small enough not to overflow conte...
This record as markdown: /tools/io-github-ajc3xc-meridian/refresh-context.md
What refresh_context does on Meridian
AI agents call refresh_context to permanently remove resources in Meridian, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
| Parameter | Type | Required | Description |
|---|---|---|---|
project_id | string | — | |
project_name | string | — | Project name — an alternative to project_id; resolved to the id internally. project_id wins if both are given. |
Parameters from the server's own tool schema.
Why refresh_context is rated Critical
An AI agent that decides to call refresh_context doesn't hesitate, doesn't double-check, and doesn't stop at one. Whatever it removes from Meridian is gone. There is no undo for destructive operations.
Attacks that exploit this kind of access
The rule that runs refresh_context safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Meridian, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For refresh_context, this is the rule to start with:
refresh_context is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Meridian, apply this rule, and every refresh_context call is checked against it from then on.
Questions about refresh_context
[SUPPORT] Single-call post-compaction recovery for planning chats. Returns a COMPACT snapshot — current sprint + progress, next pending items, the active session id, recent handoffs, high-priority (urgent) decisions, unvalidated assumptions, and key note slugs — small enough not to overflow context. Call this the moment a chat feels disoriented (e.g. right after a /compact) to re-orient in one round-trip. Persistent-state disclosure: on hosted Meridian, supplied text and project/session metadata -- including task log entries, pinned decisions, sprint items, notes, handoff/goal state, and HITL queue items -- are sent to and stored in Meridian's service, in an isolated per-tenant Postgres database (Neon); self-hosted deployments keep the same categories in the configured local SQLite/Postgres database. This data is visible in the dashboard and API, and may resurface in later project context or handoffs. Notes and pinned decisions can be deleted individually; task log entries and sprint items can be deleted via the dashboard/API (not exposed as an agent-facing tool); HITL queue items and handoff state have no per-record delete. Full removal of any of this data is available via project or account deletion, using the documented controls. Do not include secrets. It is categorised as a Destructive tool in the Meridian MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
refresh_context accepts 2 parameters: project_id, project_name. The full parameter table on this page comes from the server's own tool schema.
Register the Meridian MCP server in PolicyLayer and add a rule for refresh_context: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Meridian. Nothing to install.
refresh_context is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the refresh_context rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for refresh_context. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
refresh_context is provided by the Meridian MCP server (@meridianmcp/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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