run_watchlist_query
[SUPPORT] b924fd7c — re-run a saved watchlist query and diff its results against everything already captured for it. Every newly-seen result (matched by a per-source stable id — arxiv_id/openalex_id/s2_id/pmid/doi/core_id/sha/repo/hn_id, falling back to url) is auto-captured via the same durable ...
This record as markdown: /tools/io-github-ajc3xc-meridian/run-watchlist-query.md
What run_watchlist_query does on Meridian
AI agents invoke run_watchlist_query to trigger actions in Meridian. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| 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. |
watchlist_id | string | Yes | id returned by save_watchlist_query / list_watchlist_queries. |
Parameters from the server's own tool schema.
Why run_watchlist_query is rated High
run_watchlist_query triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs run_watchlist_query 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 run_watchlist_query, this is the rule to start with:
run_watchlist_query stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Meridian, apply this rule, and every run_watchlist_query call is checked against it from then on.
Questions about run_watchlist_query
[SUPPORT] b924fd7c — re-run a saved watchlist query and diff its results against everything already captured for it. Every newly-seen result (matched by a per-source stable id — arxiv_id/openalex_id/s2_id/pmid/doi/core_id/sha/repo/hn_id, falling back to url) is auto-captured via the same durable path as capture_research_finding/save_finding, tagged so the NEXT run recognizes it as already-seen. Returns {new_count, already_seen_count, new_results, captured, total_results}. Never raises — an unresolvable watchlist_id or a network/parse failure from the underlying search both degrade to {error}. 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 Execute tool in the Meridian MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
run_watchlist_query accepts 3 parameters: project_id, project_name, watchlist_id. Required: watchlist_id. 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 run_watchlist_query: 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.
run_watchlist_query is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run_watchlist_query 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 run_watchlist_query. 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.
run_watchlist_query 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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