$ loading_
Manage Langfuse projects, API keys, and traces through MCP locally.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "langfuse-mcp" yet — see the docs or source repo.
Use langfuse-mcp to create a project named "Customer Support Bot Monitoring" in my local Langfuse instance and return the result.
Returns the project creation result, such as confirmation and basic project identifiers.
Use langfuse-mcp to create a new API key for the project "Customer Support Bot Monitoring" and tell me the result.
Returns the API key creation result or related status information.
Use langfuse-mcp to query recent traces in my local Langfuse instance and give me a brief list.
Returns trace query results with basic information useful for debugging or analysis.
Developers or DevOps engineers can create projects and manage API keys through MCP in chat, reducing manual work in the web interface.
When a team runs a self-hosted local Langfuse v3 stack, they can use this tool to query traces for troubleshooting and runtime inspection.
In a local development setup running Langfuse v3 via Docker Compose, this MCP tool helps bring common management tasks into AI workflows.
It is an MCP server for Langfuse that lets Claude Code create projects, manage API keys, and query traces without using the web UI.
The provided information says it is designed for a self-hosted Langfuse v3 stack running locally via Docker Compose. For more specific installation and configuration requirements, see the source repository.
Its key difference is that project, API key, and trace-related tasks can be done through MCP inside chat or coding assistant workflows instead of manually switching to the web UI.
Access and manage Langfuse prompts through MCP for faster prompt workflows.
Monitor AI systems, traces, and quality metrics with Langfuse observability.
Manage Langfuse prompts, observability, and metrics through natural language workflows.
Build, debug, and manage software tasks with natural language across LLMs.
Build MCP agent workflows with NestJS, LangGraph, and flexible model orchestration.
Manage YouTrack issues, projects, and searches in natural language.