Langfuse Prompt Management MCP Server
LocalAbout Langfuse Prompt Management MCP Server
Langfuse Prompt Management MCP Server is an MCP server for accessing and managing prompts stored in Langfuse. It is intended for teams that keep prompts in Langfuse and want MCP clients to list and compile them.
Key features
- 01prompts/list for listing available prompts
- 02prompts/get for retrieving and compiling prompts
- 03Tool equivalents for clients without prompt support
- 04Supports both text and chat prompt formats
Use cases
- 01Use Langfuse prompts inside Claude Desktop
- 02Reuse managed prompts in Cursor
- 03Compile prompts with variables before sending them to a model
MCP support
This project is an MCP server that implements the MCP Prompts specification and also exposes get-prompts and get-prompt tools for MCP clients to access Langfuse prompts.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMELangfuse Prompt Management MCP Server
Model Context Protocol (MCP) Server for Langfuse Prompt Management. This server allows you to access and manage your Langfuse prompts through the Model Context Protocol.
Demo
Quick demo of Langfuse Prompts MCP in Claude Desktop (unmute for voice-over explanations):
https://github.com/user-attachments/assets/61da79af-07c2-4f69-b28c-ca7c6e606405
Features
MCP Prompt
This server implements the MCP Prompts specification for prompt discovery and retrieval.
-
prompts/list: List all available prompts- Optional cursor-based pagination
- Returns prompt names and their required arguments, limitation: all arguments are assumed to be optional and do not include descriptions as variables do not have specification in Langfuse
- Includes next cursor for pagination if there's more than 1 page of prompts
-
prompts/get: Get a specific prompt- Transforms Langfuse prompts (text and chat) into MCP prompt objects
- Compiles prompt with provided variables
Tools
To increase compatibility with other MCP clients that do not support the prompt capability, the server also exports tools that replicate the functionality of the MCP Prompts.
-
get-prompts: List available prompts- Optional
cursorparameter for pagination - Returns a list of prompts with their arguments
- Optional
-
get-prompt: Retrieve and compile a specific prompt- Required
nameparameter: Name of the prompt to retrieve - Optional
argumentsparameter: JSON object with prompt variables
- Required
Development
npm install
# build current file
npm run build
# test in mcp inspector
npx @modelcontextprotocol/inspector node ./build/index.js
Usage
Step 1: Build
npm install
npm run build
Step 2: Add the server to your MCP servers:
Claude Desktop
Configure Claude for Desktop by editing claude_desktop_config.json
{
"mcpServers": {
"langfuse": {
"command": "node",
"args": ["<absolute-path>/build/index.js"],
"env": {
"LANGFUSE_PUBLIC_KEY": "your-public-key",
"LANGFUSE_SECRET_KEY": "your-secret-key",
"LANGFUSE_BASEURL": "https://cloud.langfuse.com"
}
}
}
}
Make sure to replace the environment variables with your actual Langfuse API keys. The server will now be available to use in Claude Desktop.
Cursor
Add new server to Cursor:
- Name:
Langfuse Prompts - Type:
command - Command:
LANGFUSE_PUBLIC_KEY="your-public-key" LANGFUSE_SECRET_KEY="your-secret-key" LANGFUSE_BASEURL="https://cloud.langfuse.com" node absolute-path/build/index.js
Limitations
The MCP Server is a work in progress and has some limitations:
- Only prompts with a
productionlabel in Langfuse are returned - All arguments are assumed to be optional and do not include descriptions as variables do not have specification in Langfuse
- List operations require fetching each prompt individually in the background to extract the arguments, this works but is not efficient
Contributions are welcome! Please open an issue or a PR (repo) if you have any suggestions or feedback.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.