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competlab-mcp-server

competlab-mcp-server

by competlab
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TypeScript
Remote

start_agent_adoption_scan

Launch an async Agent Adoption Check on any domain. Runs 25 checks on discoverability, access control, content readability, and agent endpoints, returning a scanId for polling.

Instructions

Start an async Agent Adoption Check on any domain — 25 checks across discoverability, access control, content readability, and agent endpoints, per the open Agent-Adoption Specification. Returns scanId immediately; poll with get_agent_adoption_scan. Typical completion: 30-90 seconds.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "domain": "<domain>"
    },
    "name": "start_agent_adoption_scan"
  }
}

Input Schema

NameRequiredDescriptionDefault
domainYesDomain to scan, e.g. example.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv4.0.1
    • removedInput schema / additionalProperties
      Removed value: -false
  2. Addedv1.2.0

TDQS

A4.5/5.0
Behavior5/5

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

The description goes well beyond the annotations: it discloses the async nature, immediate return of a scanId, the polling workflow, the expected completion window (30-90 seconds), and the number/type of checks. This is rich behavioral context for a scan-starting tool.

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 front-loaded with the core action and compresses scope, return behavior, polling instruction, and timing into a few efficient sentences. Every clause earns its place.

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

Completeness5/5

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

For a start-scan tool with one required parameter, no output schema, and annotations that already flag mutability and open-world behavior, the description supplies all necessary context: what it does, what it returns, how to retrieve results, and how long it takes.

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 coverage is 100% and the single `domain` parameter is fully described in the schema, including an example. The description adds no new parameter semantics beyond the schema, so the baseline of 3 applies.

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 states a specific verb ('Start') and resource ('Agent Adoption Check'), names the domain scope, and lists the four check categories. It also distinguishes itself from the poll sibling by naming `get_agent_adoption_scan`, so an agent can identify it without opening schemas.

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?

It clearly establishes when to use the tool (to start a scan on a domain) and explicitly names the polling alternative with `get_agent_adoption_scan`. It does not, however, clarify when to use this over other start scans such as `start_tech_stack_scan`, so a 4 rather than 5.

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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