Lists prompt templates for engineering reasoning workflows, enabling structured thought through step-by-step reasoning, branching, merging, and validation.
Apache 2.0
147,743 tools. Last updated 2026-05-27 17:34
"Enhancing Prompt Engineering with MCP" matching MCP tools:
- Discover available prompt engineering techniques with acceptance statistics to enhance AI interactions through optimized method selection.MIT
- Improve prompt quality by applying optimal engineering techniques like chain-of-thought reasoning based on intent analysis.MIT
- Provide answers to clarifying questions to continue prompt engineering for Claude Code, enabling interactive refinement of optimized prompts.MIT
- Retrieve the capabilities exposed by an MCP server instance, including total counts and current tool, resource, and prompt surfaces. Use for server-specific exposure instead of integration-level lists.MIT
- Assign or remove a label for a specific prompt version. Use null to clear the label after looking up IDs with list_prompt_labels.MIT
Matching MCP Servers
- AlicenseAqualityBmaintenanceEnables AI agents to generate, view, and analyze engineering diagrams (RF, PCB, EMC) in draw.io using natural language prompts, with auto-layout and 269 engineering stencils.Last updated105AGPL 3.0
- Alicense-qualityBmaintenanceEnables AI coding environments to enforce engineering governance through MCP tools and resources for init, check, route, and review workflows.Last updated2MIT
Matching MCP Connectors
Cloudflare Workers MCP server: ai-prompt-optimizer
Real-time prompt injection and jailbreak detection for AI agents. Blocks instruction overrides, data exfiltration, tool poisoning and 8 attack types. Now with shared learning brain - confirmed attacks shared across the EMA network instantly. Grade A security for any AI pipeline.
- Delete a prompt and all its versions by prompt ID. Irreversible action that breaks callers using the slug; confirm removal with list_prompt_versions first.MIT
- Assembles a complete system prompt with database schema, object classes, properties, codelists, spatial context, and optional SQL examples and query guidelines.Apache 2.0
- Submit feature requests, report documentation gaps, or escalate issues to the engineering team through a direct email.ISC
- Statically analyze system prompts for prompt-injection vulnerabilities: identify untrusted placeholders, missing delimiters, dangerous instructions, and precedence inversion.MIT
- Generate engineering change notice suggestions from failure analysis data to address paste aperture changes, AVL updates, or design modifications.Apache 2.0
- Retrieve a specific prompt template from LangSmith by providing its exact name, enabling prompt reuse and management in language model workflows.MIT
- Lists Engineering Change Notices (ECNs) in a project, with optional filters by severity, status, and type.Apache 2.0
- Create an Engineering Change Order (ECO) that bundles specified ECNs, commits changes to a repository, and optionally generates a pull request.Apache 2.0
- Remind developers to consult MCP tools during Aptos blockchain development to maintain proper workflow habits and implement features correctly.Apache 2.0
- List all Engineering Change Orders (ECOs) in a project, including ECN IDs, status, and resolution summary. Filter by status to track progress.Apache 2.0
- Retrieve prompts from LangSmith with options to filter by visibility and limit results for prompt management.MIT
- Scans LLM-generated responses before delivery to block system prompt leaks, unexpected PII, toxic content, or topic drift. Provide original prompt for best results.Apache 2.0
- Run multiple generation prompts in sequence with a shared system prompt. Captures errors inline per item, returning all results with delimiters.MIT
- Analyze text for prompt injection, jailbreak attempts, data exfiltration, and social engineering threats using 42+ detection patterns to identify AI security risks.MIT