VerifyAX MCP
OfficialServer Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| VERIFYAX_API_KEY | Yes | Your VerifyAX API key |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tasks | {
"list": {},
"cancel": {},
"requests": {
"tools": {
"call": {}
}
}
} |
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_compatible_tagsA | Lists the skill tags that can be used to generate a scenario of a given type (info_exchange or interview). Use this before generating a scenario to pick valid tags. Returns each tag’s name, category, and description, and flags QnA tags that must be the only tag. |
| register_agentA | Registers an AI agent in VerifyAX given its name, connector type (A2A, API, DIRECTLINE for Copilot Studio, or MCP), URL, and optional auth or connector settings. For A2A agents it first verifies the agent card is reachable; DIRECTLINE and MCP agents are probed before creation. Returns the new agent’s uuid and whether connectivity was checked. Note: any token, Direct Line secret, or password passed here transits the conversation — prefer supplying credentials out of band where possible. |
| list_agentsA | Lists the AI agents registered in your VerifyAX workspace, optionally filtered by connector type (A2A, API, DIRECTLINE, EXTENSION, or MCP). Returns each agent’s uuid, name, type, and URL. |
| delete_agentA | Permanently deletes an agent from your VerifyAX workspace by its uuid. This cannot be undone. Returns confirmation of the deletion. |
| generate_scenarioA | Generates a new test scenario of a given type (info_exchange or interview) with optional skill tags and context. Typically takes 30s–2min; task-capable MCP clients receive a pollable task handle immediately, while others block until generation finishes. Set num_scenarios greater than 1 for batch mode (requires tag_pool). Returns the new scenario’s uuid, or batch uuids when batching, or a structured error with details if generation fails (e.g. incompatible tags). |
| list_scenariosA | Lists the test scenarios in your VerifyAX workspace, optionally filtered by type (info_exchange or interview) and status. Returns each scenario’s uuid, name, type, and status. |
| delete_scenarioA | Permanently deletes a scenario from your VerifyAX workspace by its uuid. This cannot be undone and fails if simulation runs still reference the scenario. Returns confirmation of the deletion. |
| evaluate_agentA | Runs an agent against a scenario and evaluates the result end to end. Typically takes 30s–30min; task-capable MCP clients receive a pollable task handle immediately, while others block until the evaluation completes. Give it an agent uuid and a scenario uuid; it previews cost, runs the simulation, waits for it, and returns the evaluation scores. Optional timeout_minutes (1–240) overrides the scenario default for this run. |
| list_recent_runsA | Lists recent simulation runs in your VerifyAX workspace, optionally filtered by status, agent, scenario, date range, search text, or run group. Returns each run’s uuid, status, agent, scenario, and evaluation handle. |
| get_run_detailsA | Fetches the full details of a single simulation run by its uuid, including its status and the evaluation results when they are available. Use after a run to inspect scores and outcome. |
| get_usage_summaryA | Summarizes VerifyAX usage events over an optional time range or for a specific simulation, scenario, or job. Paginates across all matching events (up to a cap) and returns the total event count, a breakdown by product area, and total platform spend in USD when the API reports it. |
| preview_run_costA | Estimates the credit cost of running an agent against a scenario before triggering it. Returns the estimated credits, your current balance, and any pending committed spend. Optional timeout_minutes (1–240) affects the run-cost estimate. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 12 tools
The set cleanly separates three resources (agents, scenarios, runs) plus usage, and list vs get vs delete verbs are clear. The only mild overlap is preview_run_cost vs evaluate_agent, but their descriptions distinguish 'estimate' from 'execute,' so an agent can pick correctly.
Every name is snake_case verb_noun (list_agents, register_agent, evaluate_agent, get_run_details, generate_scenario, etc.). The only stylistic variance is 'register_agent' instead of 'create_agent,' which is still a clear verb and consistent in form.
12 tools is well within the sweet spot for a multi-resource platform (agents, scenarios, runs, billing). Each tool maps to a distinct capability with no filler entries.
Core lifecycle is covered: agents (register/list/delete), scenarios (generate/list/delete), runs (list/get/evaluate), plus cost and usage. Minor gaps remain — no get_agent/get_scenario detail fetch, and no update operations for agents or scenarios — but agents can work around these.