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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Langfuse with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Monitor LLM apps via Langfuse. track traces, manage prompt templates, and audit evaluation scores.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 10 capabilities

The complete Langfuse capability set.

These are the exact actions your AI can choose when you ask it to work with Langfuse.

Capability set01 / 03

01-04

4 capabilities in this set.

Part of 10 available through Langfuse.

  1. 01

    List sessions

    List high-level user session entities encapsulating multiple traces

  2. 02

    Create observation

    Create a new LLM observation (span, event, generation) inside a trace

  3. 03

    Create score

    G. 1-5 stars) or automated pipeline metrics bounding exactly onto the specified Trace or Observation. Attach human feedback or evaluation metrics to a trace/observation

  4. 04

    Get trace

    Get complete telemetry and nested graph for a single trace

Capability set02 / 03

05-07

3 capabilities in this set.

Part of 10 available through Langfuse.

  1. 05

    List traces

    List all traces tracking LLM API sessions

  2. 06

    Get daily metrics

    Generate rolled-up USD cost and aggregated latency statistics

  3. 07

    List prompts

    Extract actively managed prompt templates and versions

Capability set03 / 03

08-10

3 capabilities in this set.

Part of 10 available through Langfuse.

  1. 08

    Get observation

    Retrieve explicit span or generation context within a trace

  2. 09

    List observations

    List raw observation objects spanning across traces

  3. 10

    List scores

    List all explicit scores mapping quality or cost algorithms

Observed, not estimated

842ms average. Fast in production.

Langfuse is checked daily against the live service.

Daily averagePeak 1015ms
Aug 20Today
Fastest day
684ms
Slowest day
1015ms
14-day trend
Slowing+27%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 10 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Langfuse, so you can see the experience inside your AI.

It does not authenticate your account with Langfuse. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Langfuse Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_sTXOynCd5hRTA7WbjY0nBUsTjmjwRIVY989VA7VU/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Langfuse capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "langfuse-llm-tracing-evals-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_sTXOynCd5hRTA7WbjY0nBUsTjmjwRIVY989VA7VU/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

FAQ

Questions Langfuse owners ask.

  • 01

    Can I see the exact system instruction for a specific prompt version?

    Yes. Use the list_prompts capability to browse your managed templates. Your agent can retrieve the exact text and variables for any deployed prompt version, making it easy to audit AI logic through natural conversation.

  • 02

    How do I log human feedback for a specific trace?

    Use the create_score capability by providing the Trace ID and a JSON payload defining the score name (e.g. 'user-satisfaction') and value. Your agent will attach this structured data directly to the Langfuse record.

  • 03

    Can my agent report on my LLM spending for the current day?

    Absolutely. The get_daily_metrics capability retrieves aggregated USD costs and average latency metrics from Langfuse. Your agent can summarize these statistics to help you monitor your infrastructure budget in real-time.

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