Langfuse

# Langfuse > Langfuse is an **open-source AI engineering platform** ([GitHub](https://github.com/langfuse/langfuse)) that helps teams collaboratively debug, analyze, and iterate on their LLM applications. All platform features are natively integrated to accelerate the development workflow. ## Langfuse Docs MCP Server Connect to the Langfuse Docs MCP server to access documentation directly in your AI editor: - **Endpoint**: `https://langfuse.com/api/mcp` - **Transport**: `streamableHttp` - **Documentation**: [Langfuse Docs MCP Server](https://langfuse.com/docs/docs-mcp) The MCP server provides tools to search Langfuse documentation, GitHub issues, and discussions. See the [installation guide](https://langfuse.com/docs/docs-mcp) for setup instructions in Cursor, VS Code, Claude Desktop, and other MCP clients. ## Langfuse Skill for AI Coding Agents Install the Langfuse skill before implementing anything with Langfuse. The skill provides up-to-date documentation, best-practice workflows for instrumentation, prompt management, and programmatic API access via the Langfuse CLI. Install from: [github.com/langfuse/skills](https://github.com/langfuse/skills/tree/main/skills/langfuse) ## Tracing Best Practices Before instrumenting an application with Langfuse, read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md) — it covers trace scope, observation naming, meaningful input/output, and the attributes (metadata, tags, users, sessions) that evaluators, dashboards, and experiments rely on. ## Docs For the best results, install the [Langfuse skill](https://github.com/langfuse/skills/tree/main/skills/langfuse) before using these docs. For the full list with links to each page, see: https://langfuse.com/llms-docs.txt Pages: Overview, Audit Logs, Authentication & SSO, Billable Units, Data Deletion, Data Retention, LLM Connections, Access Control (RBAC), SCIM and Org API, Spend Alerts, Troubleshooting and FAQ, Agent Skill,