intelligence-hub-mcp

by t012093

Overview Schema Source Related Servers Discussions Admin

Python

Local

list_intelligence_records

List and filter stored intelligence records by category or serendipity to retrieve relevant insights.

Instructions

Lists stored intelligence records with optional category or serendipity filtering.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_intelligence_records"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`category`	No
`is_serendipity`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 30, 2026

TDQS

B3.3/5.0

Behavior3/5

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

No annotations are present, so the description carries the disclosure burden. 'Lists stored intelligence records' makes clear this is a read-only enumeration of persisted records, with no obvious side effects, but it does not disclose ordering, pagination, or how filtering behaves beyond the parameter names.

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?

A single sentence that front-loads the action and resource, then adds the two filter options. Every phrase is functional and there is no redundant filler.

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

Completeness3/5

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

For a simple, fully optional list operation this is minimally viable, especially with an output schema present. However, the absence of usage guidance and parameter detail, combined with zero annotations, leaves some ambiguity about when to call it and what the filters accept.

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 0%, so the description must compensate. It adds that category and serendipity are filters, which helps interpret the nullable inputs, but it does not explain the limit parameter or what valid category/serendipity values look like.

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 uses a specific verb ('Lists') and a specific resource ('stored intelligence records'), and it conveys the optional filtering dimensions. It does not explicitly name sibling tools, but the wording clearly separates listing from searching or fetching a feed.

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

Usage Guidelines2/5

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

No guidance is given about when to use this tool instead of search_intelligence or fetch_intelligence_feed. The optional filters are mentioned, but there is no explanation of when to apply category vs. serendipity filtering.

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

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