QualeQuest — AI Agent Governance Platform
com.qualequest/governance
3 toolsHTTPregistry active
Summary
This server connects Claude to QualeQuest's adversarial governance system, which puts operational plans through a seven-phase trial process: filing, charges, evidence, prosecution, defense, verdict, and sentencing. You'd reach for this when you need a decision validated before committing resources, especially for AI deployments, procurement, or scaling decisions. It extracts load-bearing claims from your plan, grades supporting evidence, builds the failure case, and issues binding verdicts with tripwires. The workflow takes your decision title, plan summary, failure definition, and risk tolerance, then runs an automated trial that returns a complete packet. Think structured red-teaming as a service rather than consulting calls.
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →Tools
Public tool metadata for what this MCP can expose to an agent.
3 tools
qualitygate_validateAfter your agent generates output, validate it against your rules before shipping. Runs deterministic checks (regex, JSON schema, syntax) plus optional LLM-powered tone and factual analysis. Returns a structured verdict (pass, warn, or fail) with a 0-100 score and per-check is...7 params
After your agent generates output, validate it against your rules before shipping. Runs deterministic checks (regex, JSON schema, syntax) plus optional LLM-powered tone and factual analysis. Returns a structured verdict (pass, warn, or fail) with a 0-100 score and per-check is...
Parameters* required
check_typesarrayChecks to run. Auto-inferred if omitted.
directivesarrayDirective objects. Types: must_include, must_not_include, must_match, must_not_match, must_contain, must_not_contain, min_length, max_length.
languagestringCode language for syntax check: json, python, javascript, typescript.
outputstringThe agent output text to validate.
overridebooleanForce pass. Requires override_reason.
override_reasonstringRequired when override is true.
schemaobjectJSON Schema to validate output against.
guardrail_checkEvaluate a proposed agent action against your governance policies. Returns allow or deny with the matched policy reason. Requires at least one active policy created via guardrail_create_policy. Deterministic rule evaluation — no LLM. Costs 1 credit.2 params
Evaluate a proposed agent action against your governance policies. Returns allow or deny with the matched policy reason. Requires at least one active policy created via guardrail_create_policy. Deterministic rule evaluation — no LLM. Costs 1 credit.
Parameters* required
agent_idstringAgent identifier.
proposed_actionobjectAction to evaluate. Must contain a 'type' field. Example: {"type": "http_request", "url": "https://external.example.com"} or {"type": "file_write", "path": "/etc/config"}.
guardrail_create_policyCreate a persistent governance policy that guardrail_check evaluates on every subsequent call. Define rules using and/or/not operators over action types, resource patterns, and budget thresholds. Call this before using guardrail_check — checks require at least one active polic...5 params
Create a persistent governance policy that guardrail_check evaluates on every subsequent call. Define rules using and/or/not operators over action types, resource patterns, and budget thresholds. Call this before using guardrail_check — checks require at least one active polic...
Parameters* required
action_typesarrayOptional. Restrict this policy to only evaluate when proposed_action.type matches one of these values. Examples: ['file_write', 'api_call', 'db_delete']. Omit to apply the policy to all action type...
descriptionstringOptional human-readable summary of what this policy enforces. Returned in guardrail_check responses and guardrail_list_policies output for auditability.
namestringUnique policy name per org. Examples: 'no-delete-in-prod', 'budget-cap-50', 'pii-block'.
prioritynumberOptional. Evaluation order. Default: 0.
rulesarrayArray of rule objects evaluated against the proposed_action in guardrail_check. Leaf operators: eq, starts_with, contains, gt, lt (compare field to value). Compound operators: and, or, not (nest su...
Featured
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →Categories
Registryactive
TransportHTTP
UpdatedApr 5, 2026
