Skip to main content
Glama
AiAgentKarl

shared-context-cache-mcp-server

cache_search

Search the shared cache by keywords to find verified, reusable results from other agents, reducing token cost and avoiding redundant computation.

Instructions

Search the shared cache by keywords. Find relevant cached results from other agents.

Search before computing -- if another agent has cached a similar result, you can reuse it directly. Results include trust scores showing verification level.

Args: query: Keywords to search for (e.g. 'weather berlin', 'bitcoin price') limit: Max number of results to return (default: 10, max: 50)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must cover behavioral aspects. It mentions that results include trust scores, but does not disclose if the search is read-only, any side effects, or performance characteristics. This leaves some gaps.

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?

The description is concise, with the purpose and guideline in the first two lines, followed by a structured 'Args' section. Every sentence adds value without redundancy.

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?

The description covers purpose, parameters, and usage guideline adequately. With an output schema present, it does not need to detail return values, but it could mention ordering or pagination for completeness.

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

Parameters5/5

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

Schema description coverage is 0%, but the description compensates fully with an 'Args' section that explains the 'query' parameter with examples and the 'limit' parameter with default and max values, adding meaning beyond the schema's type information.

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?

The description clearly states the verb 'Search' and the resource 'shared cache', specifying that it finds relevant cached results from other agents. This distinguishes it from siblings like cache_list or cache_lookup, which likely do not perform keyword search.

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

Usage Guidelines4/5

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

The description advises using this tool before computing to reuse cached results, providing a clear when-to-use context. However, it does not explicitly mention when not to use it or compare to alternatives like cache_lookup for specific keys.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AiAgentKarl/shared-context-cache-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server