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AI Data MCP

by ResetFull
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TypeScript
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List MongoDB connections

mongo_list_connections
Read-onlyIdempotent

List configured MongoDB connection IDs, environments, databases, and effective access modes to inspect available targets without exposing URIs or credentials.

Instructions

List configured MongoDB connection IDs, environments, databases, and effective access modes. Connection URIs and credentials are never returned.

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": "mongo_list_connections"
  }
}

Input Schema

NameRequiredDescriptionDefault
response_formatNomarkdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0-alpha.1

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds a genuinely useful trait annotations cannot express: that URIs and credentials are never returned, defining the data-exposure boundary of the response.

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, zero filler, with the returned-field list front-loaded before the security caveat. Every clause earns its place.

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?

There is no output schema, and the description compensates by enumerating the returned fields. For a parameterless read-only listing tool this is nearly sufficient; only pagination/ordering behavior is unaddressed.

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%, but the sole parameter (response_format) has an enum of two self-explanatory values and a documented default, so little is actually ambiguous. The description adds no meaning beyond the schema, but the gap it leaves is trivial.

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?

States a specific verb (List) and resource (configured MongoDB connections) and even enumerates the fields returned (IDs, environments, databases, access modes). It is clearly distinct from the mysql_* and redis_* siblings by resource, but never names an alternative, so cross-sibling routing is left implicit.

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?

The description gives no when-to-use, when-not-to-use, or prerequisite context — nothing tells the agent to call this before mongo_find/mongo_aggregate to discover valid connection IDs. Usage is only inferable from the verb.

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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