Skip to main content
Glama
lhswgzy

free-search-mcp-ts

by lhswgzy

Inspect or maintain the local index

local_index
DestructiveIdempotent

Report, prune, clear, or compact the local cache of fetched pages and search responses to control disk use and remove stale data. Use stats for safe checks; clear and prune delete permanently.

Instructions

Report on, prune, clear or compact the local cache that stores fetched pages and recent engine responses. stats is safe and cheap; clear and prune delete data permanently.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNoFor `clear`: what to delete (default all).
actionNostats (default) reports sizes; clear empties the cache; prune drops entries older than max_age_days or beyond max_pages; vacuum compacts the database file.
formatNoOutput format. "markdown" (default) is compact and readable; "json" returns structured data for post-processing.
max_pagesNoFor `prune`: keep only this many of the most recently fetched pages.
max_age_daysNoFor `prune`: drop pages fetched more than this many days ago.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already flag destructiveHint=true and readOnlyHint=false, but they are tool-level and cannot say that the danger is confined to specific actions. The description adds per-action detail by naming `stats` as safe and `clear`/`prune` as permanently deleting data, which is genuinely useful disambiguation. It doesn't cover what `vacuum` does or what stats returns, so it stops short of a 5.

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?

Two sentences, front-loaded with the capability and immediately followed by the safety-relevant distinction. Every clause earns its place and nothing is padded.

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 an action-dispatch maintenance tool with 5 optional params and no output schema, the description covers purpose and the primary risk (permanent deletion). It could say more about what `stats` reports or how `vacuum` differs, but with 100% schema coverage and destructive annotations, the essentials are present.

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%, and the schema fully documents scope, action, format, max_pages, and max_age_days. The description only echoes the action names already enumerated in the schema, adding no syntax, defaults, or interaction detail beyond it, so the baseline 3 applies.

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

Purpose4/5

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

The description pairs concrete verbs (report, prune, clear, compact) with a specific resource: the local cache of fetched pages and recent engine responses. This is far more than a restatement of the name, though it never names or differentiates itself from siblings like search_index or list_engines.

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

Usage Guidelines3/5

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

The line '`stats` is safe and cheap; `clear` and `prune` delete data permanently' hints at action selection, but there is no explicit 'use this when' guidance and no comparison to the sibling index/engine tools. The agent must infer that destructive maintenance is only warranted in specific situations.

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