Skip to main content
Glama
alidade-ai

Alidade MCP

Official
by alidade-ai

List saved searches

list_saved_searches
Read-only

Retrieve workspace-shared and curated saved searches, each bundling entity comparison groups, platform, date range, and keyword filters; use the returned ID with analytics or mention search tools.

Instructions

List the saved searches available to the workspace (workspace-shared plus Alidade-curated). A saved search bundles comparison groups of entities, a platform filter, a date range, and keyword filters — pass its id as savedSearchId to get_analytics or search_mentions. This is the recommended starting point for analytics questions.

Input Schema

NameRequiredDescriptionDefault
cursorNoOpaque pagination cursor from a previous response's `nextCursor`. Use the same query parameters across paged requests.
searchNoFilter saved searches by name (case-insensitive).
pageSizeNoItems per page (max 100, default 25).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds genuine context about curation scope (workspace-shared vs Alidade-curated), but says nothing about pagination behavior, result ordering, or what the workspace sees when a saved search is curated vs user-created.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences: scope first, resource definition second, downstream routing third. Every clause carries information an agent needs, and the recommended-use cue is placed where it will be read.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-required-parameter read tool with 100% schema coverage and no output schema, the description supplies the conceptual model (what a saved search bundles) and where to go next. The only real gap is return-shape/pagination behavior, which the schema partially covers via nextCursor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (cursor, search, pageSize are all documented in-schema), so the baseline is 3. The description does not add any further meaning about how the name filter or paging interacts with the curated/workspace-shared split.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (list) and resource (saved searches) with explicit scope: workspace-shared plus Alidade-curated. It also defines what a saved search contains (comparison groups, platform filter, date range, keyword filters), which distinguishes it from the sibling get_saved_search (single item) and from create/update/delete_saved_search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to pass the returned id as savedSearchId to get_analytics or search_mentions, and declares itself "the recommended starting point for analytics questions." That names the alternatives and the condition that selects them, leaving little to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.