list_agents
Read-only
Agent Sprawl Radar: list discovered AI agents, MCP servers, bots, workflows, risk levels, and owners.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| risk_level | No |
MCP Verify
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- Added
TDQS
C2.9/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description adds the 'discovered' scoping trait, implying only previously discovered items are returned, but offers no details on pagination, ordering, or output structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with the key action upfront. The 'Agent Sprawl Radar' label is catchy but slightly extraneous, costing a point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and sparse annotations, the description fails to fully specify what the list contains, how to filter, or pagination behavior. The current text mixes entities and attributes, leaving the return structure unclear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the 'limit' or 'risk_level' parameters. 'risk_level' appears as 'risk levels' in the description, hinting at filtering, but it's not explicit.
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 the verb 'list' and specifies the resource: 'discovered AI agents, MCP servers, bots, workflows, risk levels, and owners.' It distinguishes from siblings like get_agent (singular) and list_high_risk_agents (risk-specific) by implying a broad inventory, though the mix of entity types is slightly ambiguous.
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 on when to use this tool vs alternatives. Sibling tools like get_agent and list_high_risk_agents exist, but the description doesn't mention them or any prerequisites/exclusions.
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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TDQS
B3.4/5.0
Disambiguation4/5
Most tools target distinct resources and actions (e.g., get_agent vs. get_drift_report). A few pairs like search/search_servers and fetch/get_server_report overlap in intent, but descriptions clarify differences in output and purpose. Agents may need to read carefully but can generally tell tools apart.
Naming Consistency4/5
Nearly all tool names follow a verb_noun snake_case pattern (list_agents, create_mandate, export_policy). The bare aliases 'fetch' and 'search' deviate slightly, but are clearly intentional, and there is no mix of camelCase or other styles. Overall consistent and predictable.
Tool Count3/5
22 tools is on the heavy side, falling into the '16-25' borderline range. While each tool appears to serve a distinct function, the set could be consolidated (e.g., the multiple 'get_*_options' tools). It is not excessive enough to be chaotic, but it is above the ideal 3-15 range.
Completeness4/5
The tool surface covers core workflows for server search, comparison, report generation, policy export, mandate creation, agent risk management, and decision-making. Minor gaps exist, such as no create/update/delete for most resources and no subscription creation, but the domain is read/decision-heavy and core lifecycle coverage is adequate.