save_watchlist_query

SERVERMeridian SOURCE@meridianmcp/mcp

Medium RISK CLASS

Category Write

Parameters 72 required

Recommended Rate-limitedsee the rule below

Registry record Grade D, identity unverified Pull the record →

This record as markdown: /tools/io-github-ajc3xc-meridian/save-watchlist-query.md

WHAT IT DOES

What save_watchlist_query does on Meridian

AI agents use save_watchlist_query to create or update resources in Meridian, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Meridian environment.

Parameter	Type	Required	Description
`name`	string	—	Optional short label for the watchlist note's title (defaults to the query text).
`limit`	integer	—	Max results per run (default 10, max 50).
`query`	string	Yes	The search terms to re-run each time.
`sort_by`	string	—	Sort order for each run (default relevance).
`project_id`	string	—
`source_type`	string	Yes	Which source this watchlist re-runs against.
`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.

RISK

Why save_watchlist_query is rated Medium

An AI agent can call save_watchlist_query faster than any human can review: one bad instruction and it creates or modifies resources in Meridian by the hundred, each call as confident as the last.

Risk signalsBulk/mass operation — affects multiple targets

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs save_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 save_watchlist_query, this is the rule to start with:

save_watchlist_query Rate-limited

save_watchlist_query stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "save_watchlist_query": {
      "limits": [
        {
          "counter": "save_watchlist_query_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Meridian, apply this rule, and every save_watchlist_query call is checked against it from then on.

FAQ

Questions about save_watchlist_query

What does the save_watchlist_query tool do? +

[SUPPORT] b924fd7c — save a recurring research query so it can be re-run and diffed over time via run_watchlist_query. Persisted as a project note (no separate table); the returned watchlist_id addresses it. Every paper_search source ('arxiv', 'openalex', 'semantic_scholar', 'pubmed', 'crossref', 'core' — core needs CORE_API_KEY) is available, plus 'github_code'/'github_repo' (meridian.github_search) and 'hn' (meridian.social_search). 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 Write tool in the Meridian MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does save_watchlist_query accept? +

save_watchlist_query accepts 7 parameters: name, limit, query, sort_by, project_id, source_type, project_name. Required: query, source_type. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on save_watchlist_query? +

Register the Meridian MCP server in PolicyLayer and add a rule for save_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.

What risk level is save_watchlist_query? +

save_watchlist_query is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit save_watchlist_query? +

Yes. Add a rate_limit block to the save_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.

How do I block save_watchlist_query completely? +

Set action: deny in the PolicyLayer policy for save_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.

What MCP server provides save_watchlist_query? +

save_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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