---
title: Agentic Prompt Management
sidebarTitle: Agent Access
description: Let AI agents retrieve, create, migrate, and update Langfuse prompts through the Agent Skill, CLI, or MCP server.
---

# Agentic Prompt Management

AI agents can work with your Langfuse prompt library while they edit application code. There are different ways for agents to access your data:

## Choose an access method

| Agent capabilities                         | Recommended access                                                                                                                                                                                                                    |
| ------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Can install tools and run shell commands   | Install the [Langfuse Agent Skill](/docs/api-and-data-platform/features/agent-skill). It teaches the agent Langfuse workflows and uses the [Langfuse CLI](/docs/api-and-data-platform/features/cli) to query and update project data. |
| Cannot install tools or run shell commands | Connect the [Langfuse MCP server](/docs/api-and-data-platform/features/mcp-server) to expose Langfuse operations as tools.                                                                                                            |
| Runs as part of a script or CI/CD pipeline | Use the [Langfuse CLI](/docs/api-and-data-platform/features/cli) directly or call the [Public API](/docs/api-and-data-platform/features/public-api).                                                                                  |

## Example workflows

Ask your agent to:

- Migrate hardcoded prompts from a codebase to Langfuse
- Retrieve a prompt and compare its latest versions
- Create a new text or chat prompt version
- Promote a tested prompt version by updating its deployment labels

## Work across Langfuse

Agents can also [investigate production behavior](/docs/observability/features/agentic-access) and [run evaluation workflows](/docs/evaluation/agentic-access) in Langfuse.

## Related guides and blog posts

- [Automatically improve prompts with Agent Skills](/blog/2026-02-16-prompt-improvement-claude-skills) — Use the Langfuse skill to analyze trace feedback and iteratively improve your prompts.
- [Headless Langfuse from your coding agent](/guides/videos/headless-langfuse) — Instrument an application, analyze traces, build a dataset, and run evaluations without leaving your coding agent.

<!-- agent-instructions -->

---

## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/docs/prompt-management/features/agentic-access.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.