Behavioral intelligence MCP server for AI agents. Exposes tools for behavioral assessment, profile management, and adaptation instructions based on DECF personality drives.
Maverick MCP has significant definition quality gaps. Tool names lack clear action verbs (maverick_assess, maverick_profile, maverick_adapt are domain-specific but not verb-noun patterns). Descriptions are present but generic, most under 200 chars and lack WHEN/WHY context. Input schemas exist but are minimal: maverick_assess has an empty 'properties' object for 'answers', maverick_profile has empty input schema, and parameter descriptions are sparse. No output schemas documented. Error handling is minimal, responses use generic 'status' fields without recovery guidance. The server reads/writes local YAML files without validation or permission checks. No tool annotations (readOnlyHint, destructiveHint, idempotentHint) despite clear read/write distinctions.
Get behavioral adaptation instructions for the current task. Returns prompt injection text and settings that the agent should follow to match the user's behavioral style. Call at the start of each new task or conversation.
Run a 2-minute behavioral assessment to detect the developer's profile, or score previously collected answers. Call with no args to get the questions, or with {answers: {1: 'a', 2: 'b', ...}} to score and save the profile.
Generate a shareable Developer Card from the user's behavioral profile. Creates a beautiful HTML file at ~/.maverick/card.html that the user can open in a browser, screenshot, and share on social media.
Record user feedback to refine the behavioral profile over time. The agent should call this when: user explicitly says the response was too long/short, user overrides a decision the agent made autonomously, user asks for more/less detail, user expresses frustration with pacing.
Get the current user's behavioral profile including drives, role (expander/converter/stabilizer), and style description.
Input schemas lack proper type definitions and property constraints. maverick_assess.answers has empty 'properties' object; maverick_profile has no input schema at all.
No output schemas documented. LLMs cannot plan downstream calls or extract required fields. Responses use generic 'status' and 'message' fields without structured typing.
Tool names do not follow verb_noun convention. 'maverick_assess', 'maverick_profile', 'maverick_adapt' are domain-specific but lack clear action verbs (get_, create_, update_, run_). LLMs struggle to infer intent from names alone.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 43 | 2026-07-28+ | v2 |
No tool annotations (readOnlyHint, destructiveHint, idempotentHint). maverick_assess, maverick_card, and maverick_feedback are WRITE operations; maverick_profile and maverick_adapt are READ_ONLY. Agents cannot distinguish safe from destructive calls.
Error responses lack recovery guidance. 'no_profile' and 'error' status codes do not tell the LLM what to do next.