Research-backed lint + generation for agent context files (CLAUDE.md, AGENTS.md) + prompt enhancer.
| Endpoint | https://mcp.promptarch.ai/mcp (streamable-http) |
|---|---|
| Registry version | 1.2.0 |
| Now | 4 tools · grade A (96) · pin ts_4a623869f389dd4aad7ca97ba7983f79 · protocol 2025-06-18 |
| First / last listed | 2026-10-25 01:20 UTC / 2026-10-25 01:20 UTC |
| Grade over time | 2026-10-25: A (96), 4 tools |
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Tools: promptarch_lint_artifact promptarch_list_artifact_types promptarch_generate_artifact promptarch_enhance_prompt
promptarch_lint_artifact | Lint an AI agent context file (CLAUDE.md, .claude/rules/ files, AGENTS.md, Cursor rules, Copilot instructions, memory files) with PromptArch's deterministic linter: ~30 research-backed rule families covering current-model anti-patterns (tool-forcing, reasoning-echo, sycophancy triggers, contradictions), per-tool size budgets, secrets/dangerous commands, and hidden-Unicode injection ("Rules File Ba params: content*, format, filename |
promptarch_list_artifact_types | List the artifact types promptarch_generate_artifact can produce from a project description. params: none |
promptarch_generate_artifact | Generate an AI agent context artifact (e.g. context_pack, claude_md) from a project description. Requires a PromptArch API key configured as an Authorization: Bearer pk_... header on this MCP server. Consumes credits. params: artifact*, project_name*, project_description*, tech_stack, repo_structure, commands, coding_conventions, target_model |
promptarch_enhance_prompt | Enhance a raw prompt with PromptArch's Prompt Enhancer: PromptArch asks 1-3 targeted clarifying questions, then rewrites the prompt from the person's answers, optimized for target_model. If this client supports MCP elicitation, the questions appear to the person as a form inside this call. Otherwise call once with just `prompt` to get the questions (free), ask the person, and call again with `ques params: prompt*, target_model, questions, answers |
Entries describe changes in tool definitions. They are not statements about a server, its quality or its author. The grade measures how the tool definitions fit model providers (token cost, schema compatibility, confusable names) as scored by the ToolFit engine at the time of the listing. JSON: append .json. Opt-out: how or hello@youraitools.co.