# PromptOT > Prompt management platform for LLM applications. Build, version, evaluate, and deliver system prompts via API — without redeploying your app. PromptOT treats LLM system prompts as structured, versioned assets. Prompts compose from typed blocks (role, context, instructions, guardrails, output_format) with `{{variable}}` interpolation, and ship to production through a REST API or the PromptOT MCP server. ## Documentation - [Docs](https://www.promptot.com/docs): Quickstart, concepts, and platform overview - [API Reference](https://www.promptot.com/docs/api): Prompt delivery and management endpoints - [MCP Overview](https://www.promptot.com/docs/mcp): Model Context Protocol server for AI assistants - [MCP Install](https://www.promptot.com/docs/mcp/install): Per-client installation steps - [MCP Tools](https://www.promptot.com/docs/mcp/tools): 23 tools across prompts, blocks, variables, versions, test cases - [MCP Scopes](https://www.promptot.com/docs/mcp/scopes): OAuth scope reference - [MCP OAuth](https://www.promptot.com/docs/mcp/oauth): OAuth 2.1 + PKCE flow - [MCP Troubleshooting](https://www.promptot.com/docs/mcp/troubleshooting): Common install and connection issues ## Product - [Pricing](https://www.promptot.com/pricing): Plans and usage limits - [Library](https://www.promptot.com/library): Prompt gallery - [Tools](https://www.promptot.com/tools): Free prompt utilities - [Token Counter](https://www.promptot.com/tools/token-counter): Estimate token usage for any prompt - [Prompt Structurer](https://www.promptot.com/tools/prompt-structurer): Convert raw prompts into structured blocks - [Prompt Analyzer](https://www.promptot.com/tools/prompt-analyzer): Score prompt quality and suggest improvements - [Changelog](https://www.promptot.com/changelog): Recent product updates - [Status](https://www.promptot.com/status): System availability ## Glossary - [Prompt Management](https://www.promptot.com/glossary/prompt-management): The practice of organizing, versioning, testing, and deploying LLM prompts through a centralized platform rather than embedding them directly in application… - [System Prompt](https://www.promptot.com/glossary/system-prompt): A special instruction provided to an LLM at the beginning of a conversation that defines its behavior, personality, constraints, and output format for the… - [Prompt Versioning](https://www.promptot.com/glossary/prompt-versioning): The practice of maintaining a complete history of changes to LLM prompts, enabling teams to compare versions, roll back to previous states, and manage… - [Prompt Injection](https://www.promptot.com/glossary/prompt-injection): A security attack where malicious input is crafted to override or manipulate an LLM's system prompt, causing the model to ignore its instructions and perform… - [Chain-of-Thought Prompting](https://www.promptot.com/glossary/chain-of-thought): A prompting technique that instructs the LLM to break down complex problems into intermediate reasoning steps before producing a final answer, significantly… - [Few-Shot Prompting](https://www.promptot.com/glossary/few-shot-prompting): A prompting technique where one or more input-output examples are included in the prompt to demonstrate the desired behavior, format, or reasoning pattern for… - [Zero-Shot Prompting](https://www.promptot.com/glossary/zero-shot-prompting): A prompting approach where the LLM is given only instructions and context without any input-output examples, relying entirely on the model's pre-trained… - [Prompt Template](https://www.promptot.com/glossary/prompt-template): A reusable prompt structure containing variable placeholders (e.g., {{user_name}}, {{context}}) that are dynamically filled at runtime, enabling the same… - [LLM Evaluation](https://www.promptot.com/glossary/llm-evaluation): The systematic process of measuring the quality, accuracy, safety, and reliability of LLM outputs against defined criteria, using automated metrics, human… - [Prompt Optimization](https://www.promptot.com/glossary/prompt-optimization): The iterative process of refining prompts to maximize output quality, consistency, and efficiency, typically through systematic testing, evaluation, and… - [Guardrails](https://www.promptot.com/glossary/guardrails): Safety constraints and behavioral boundaries embedded in prompts or applied as post-processing layers to prevent LLMs from generating harmful, off-topic, or… - [Prompt Engineering](https://www.promptot.com/glossary/prompt-engineering): The discipline of designing, structuring, and iterating on instructions given to LLMs to elicit accurate, consistent, and useful outputs for specific use cases. - [Retrieval-Augmented Generation (RAG)](https://www.promptot.com/glossary/rag): An architecture pattern that enhances LLM responses by retrieving relevant documents from an external knowledge base and including them in the prompt as… - [Prompt A/B Testing](https://www.promptot.com/glossary/prompt-ab-testing): The practice of running two or more prompt variants simultaneously on live traffic to statistically determine which version produces better outcomes against… - [Context Window](https://www.promptot.com/glossary/context-window): The maximum number of tokens (input plus output) that an LLM can process in a single request, which determines how much information can be included in a… - [Prompt Lifecycle](https://www.promptot.com/glossary/prompt-lifecycle): The complete set of stages a prompt goes through from initial authoring and iteration, through testing and review, to deployment in production, and ongoing… - [Prompt Registry](https://www.promptot.com/glossary/prompt-registry): A centralized catalog of all prompts within an organization, providing a single source of truth for discovery, access control, and operational visibility… - [Prompt Deployment](https://www.promptot.com/glossary/prompt-deployment): The process of promoting a tested and approved prompt version from a development or staging state to production, making it available to live applications… - [Prompt Governance](https://www.promptot.com/glossary/prompt-governance): The set of policies, controls, and processes that organizations implement to manage prompt changes at scale, ensuring consistency, compliance, and… - [LLMOps](https://www.promptot.com/glossary/llmops): The set of practices, tools, and workflows for operationalizing large language model applications in production, covering prompt management, evaluation… - [Prompt Testing](https://www.promptot.com/glossary/prompt-testing): The systematic validation of prompt behavior before deployment, using test cases, automated assertions, and evaluation criteria to catch regressions and… - [Prompt Evaluation](https://www.promptot.com/glossary/prompt-evaluation): The process of measuring prompt quality against defined criteria such as accuracy, relevance, safety, and format compliance, distinct from broader LLM… - [Model-Agnostic Prompts](https://www.promptot.com/glossary/model-agnostic-prompts): Prompts designed to produce consistent, high-quality results across different LLM providers and model versions, reducing vendor lock-in and enabling flexible… - [Prompt Chaining](https://www.promptot.com/glossary/prompt-chaining): A technique where multiple prompts are connected in sequence, with the output of one prompt serving as input to the next, enabling complex multi-step… - [Prompt Caching](https://www.promptot.com/glossary/prompt-caching): The practice of storing and reusing LLM responses for identical or semantically similar prompt inputs, reducing latency and cost by avoiding redundant model… - [Token Optimization](https://www.promptot.com/glossary/token-optimization): Techniques for reducing the number of tokens consumed by prompts and responses while maintaining output quality, directly lowering costs and improving… - [Structured Prompts](https://www.promptot.com/glossary/structured-prompts): Prompts organized into typed, labeled sections or blocks — such as role, context, instructions, guardrails, and output format — rather than written as a… - [Prompt Collaboration](https://www.promptot.com/glossary/prompt-collaboration): The practice of multiple stakeholders — prompt engineers, product managers, domain experts, and developers — working together on prompt development through… - [Prompt API](https://www.promptot.com/glossary/prompt-api): A REST or HTTP interface that allows applications to fetch, manage, and deliver prompts programmatically, decoupling prompt content from application code and… - [Environment-Scoped Prompts](https://www.promptot.com/glossary/environment-scoped-prompts): A deployment strategy where the same prompt identifier serves different versions depending on the requesting environment — development, staging, or production… - [Draft/Published Workflow](https://www.promptot.com/glossary/draft-published-workflow): A two-state prompt lifecycle where prompts exist as editable drafts during development and become immutable published versions when promoted to production… - [Prompt Rollback](https://www.promptot.com/glossary/prompt-rollback): The ability to revert a production prompt to a previously published version when issues are detected, providing a rapid recovery mechanism that does not… - [Prompt Compilation](https://www.promptot.com/glossary/prompt-compilation): The process of assembling structured prompt blocks — role, context, instructions, guardrails, output format — into a single prompt string, including ordering… - [Prompt Blocks](https://www.promptot.com/glossary/prompt-blocks): Typed, independently editable sections that compose a structured prompt, where each block has a designated purpose such as role definition, context… - [AI Guardrails](https://www.promptot.com/glossary/ai-guardrails): Safety constraints, behavioral boundaries, and policy enforcement mechanisms applied to AI systems to prevent harmful outputs, ensure compliance, and maintain… - [Variable Interpolation](https://www.promptot.com/glossary/variable-interpolation): The process of replacing placeholder tokens (such as {{variable_name}}) in a prompt template with actual runtime values, enabling dynamic prompts that adapt… ## Comparisons - [PromptOT vs PromptLayer](https://www.promptot.com/compare/promptot-vs-promptlayer): Compare PromptOT and PromptLayer for prompt management. See how they differ on structured composition, versioning, API delivery, evaluation, and pricing. - [PromptOT vs Langfuse](https://www.promptot.com/compare/promptot-vs-langfuse): Compare PromptOT and Langfuse for LLM prompt management. See how they differ on prompt composition, observability, tracing, evaluation, and open-source vs… - [PromptOT vs Humanloop](https://www.promptot.com/compare/promptot-vs-humanloop): Compare PromptOT and Humanloop for prompt management. See how they differ on structured composition, evaluation, deployment workflows, and enterprise features. - [PromptOT vs Braintrust](https://www.promptot.com/compare/promptot-vs-braintrust): Compare PromptOT and Braintrust for LLM development. See how they differ on prompt management, evaluation, logging, AI proxy, and developer experience. - [PromptOT vs Pezzo](https://www.promptot.com/compare/promptot-vs-pezzo): Compare PromptOT and Pezzo for prompt management. See how they differ on prompt composition, open-source availability, observability, and developer experience. - [PromptOT vs LangSmith](https://www.promptot.com/compare/promptot-vs-langsmith): Compare PromptOT and LangSmith for prompt management. See how they differ on structured composition, tracing, evaluation, LangChain integration, and developer… - [PromptOT vs Maxim AI](https://www.promptot.com/compare/promptot-vs-maxim-ai): Compare PromptOT and Maxim AI for LLM development. See how they differ on prompt management, automated testing, monitoring, and quality assurance. - [PromptOT vs Arize AI](https://www.promptot.com/compare/promptot-vs-arize-ai): Compare PromptOT and Arize AI for LLM development. See how they differ on prompt management, ML observability, production monitoring, and troubleshooting. - [PromptOT vs Latitude](https://www.promptot.com/compare/promptot-vs-latitude): Compare PromptOT and Latitude for prompt engineering. See how they differ on structured composition, collaborative editing, open-source, and AI-assisted… - [PromptOT vs Agenta](https://www.promptot.com/compare/promptot-vs-agenta): Compare PromptOT and Agenta for LLM development. See how they differ on prompt management, evaluation, open-source, playground experimentation, and deployment. - [PromptOT vs Portkey](https://www.promptot.com/compare/promptot-vs-portkey): Compare PromptOT and Portkey for LLM infrastructure. See how they differ on prompt management, AI gateway, load balancing, caching, and observability. - [PromptOT vs Mirascope](https://www.promptot.com/compare/promptot-vs-mirascope): Compare PromptOT and Mirascope for prompt engineering. See how they differ on UI-based management, code-level SDKs, type safety, and developer workflow. ## Use Cases - [Customer Support](https://www.promptot.com/use-cases/customer-support): Customer support prompts that stay consistent at scale - [Code Review](https://www.promptot.com/use-cases/code-review): Code review prompts that catch bugs, not just style issues - [Content Writing](https://www.promptot.com/use-cases/content-writing): Content writing prompts that maintain voice and structure - [Data Analysis](https://www.promptot.com/use-cases/data-analysis): Data analysis prompts that produce actionable insights - [Email Assistant](https://www.promptot.com/use-cases/email-assistant): Email assistant prompts that match tone and context - [API Documentation](https://www.promptot.com/use-cases/api-documentation): API documentation prompts that generate clear, complete references - [Chatbot](https://www.promptot.com/use-cases/chatbot): Chatbot prompts that stay on-topic and on-brand - [Summarization](https://www.promptot.com/use-cases/summarization): Summarization prompts that extract what matters ## MCP Clients - [Claude Desktop](https://www.promptot.com/mcp/claude-desktop): Install PromptOT MCP for Claude Desktop by Anthropic - [Cursor](https://www.promptot.com/mcp/cursor): Install PromptOT MCP for Cursor by Anysphere - [Codex CLI](https://www.promptot.com/mcp/codex-cli): Install PromptOT MCP for Codex CLI by OpenAI - [Windsurf](https://www.promptot.com/mcp/windsurf): Install PromptOT MCP for Windsurf by Codeium - [Zed](https://www.promptot.com/mcp/zed): Install PromptOT MCP for Zed by Zed Industries - [claude.ai](https://www.promptot.com/mcp/claude-ai): Install PromptOT MCP for claude.ai by Anthropic - [ChatGPT](https://www.promptot.com/mcp/chatgpt): Install PromptOT MCP for ChatGPT by OpenAI - [Generic stdio client](https://www.promptot.com/mcp/generic): Install PromptOT MCP for Generic stdio client by any ## Blog - [Blog Index](https://www.promptot.com/blog): Articles on prompt engineering, LLM ops, and PromptOT ## Company - [About](https://www.promptot.com/about): Team and mission - [Careers](https://www.promptot.com/careers): Open roles - [Security](https://www.promptot.com/security): Security practices and compliance - [Contact](https://www.promptot.com/contact): Get in touch - [Privacy](https://www.promptot.com/privacy) - [Terms](https://www.promptot.com/terms)