Langfuse and SuperPrompts overlap on the prompt-management surface but answer different problems.
Langfuse is an open-source observability platform: tracing, evaluation, metrics, and prompt management bundled in one tool. Prompts are one feature alongside agent tracing, LLM-as-judge evaluators, datasets, and ClickHouse-backed analytics. If you need observability and prompt management, and especially if you need to self-host, Langfuse is the answer.
SuperPrompts does prompt management as the whole product. A prompt is a set of named sections with {{ variables }}; every save is a content-addressed version; production points at one of them; your app reads it over REST, the Node SDK, or through an MCP server from Claude Code or Cursor. No tracing. No evals. No self-hosting.
The open-source question
Langfuse is Apache-2.0 and self-hostable via Docker, Helm, or Terraform on AWS/GCP/Azure. For regulated industries, data residency requirements, or teams that prefer to run their own infrastructure, this is the deciding factor. We don't offer self-hosting and have no plans to in the near term.
If self-hosting is a hard requirement, pick Langfuse. If it is a nice-to-have, the question is whether you'd rather run one more service or skip one.
Where Langfuse is stronger
Langfuse ships an evaluation surface we do not have: datasets, LLM-as-judge scorers, experiments, and links from prompt versions to production traces so you can see cost and latency per version. It also has webhooks on prompt changes and protected labels for safer production promotion. If your real problem is "I need to see what my LLM system is doing in production", Langfuse is purpose-built for that and prompts come along for free.
Where SuperPrompts is stronger
It is smaller, and that is the point. The editor works in sections so a diff shows which rule changed rather than one giant text blob. Variables are detected as you type and listed by the API, so the code that fills them in cannot silently drift from the prompt. The MCP server is one claude mcp add command and exposes read, write and publish tools, so the agent that is already editing your code can edit the prompt it depends on. And the price is a small team's price: EUR 9.99 a month for unlimited projects, prompts and users, versus $29 to $199 for Langfuse's paid tiers.
We also ship Prompt Guard, an optional set of anti-injection instructions appended to served prompts. Langfuse can surface injection attempts via tracing but does not modify what you serve.
The pricing reality
Langfuse pricing is by usage (units), not seats. Hobby is free for small projects (50k units, 2 users). Core at $29/mo gets you 100k units, unlimited users, and 90-day data retention. Pro at $199/mo unlocks 3-year retention and high rate limits. That is fair for a tracing platform: you pay for the events you store.
SuperPrompts has no events to store, so there is one paid plan. Free covers one project with five prompts and 60 API requests a minute; Pro removes every limit and adds the multi-provider playground and AI-assisted optimization.
Honest summary
Pick Langfuse if you need self-hosting, observability is part of the same purchase, or evaluations are part of how your team ships prompts. Pick SuperPrompts if prompts are the whole problem, you want them editable from Claude Code or Cursor, and you'd rather pay a small flat fee than run a tracing platform alongside. Read more in REST API vs hardcoded prompts and why version control matters for AI prompts.
SuperPrompts keeps versioned system prompts behind one REST call, with a Node SDK and an MCP server for Claude Code and Cursor. Try it free.