Langfuse (LLM Tracing & Evals) MCP Server for Cline 10 tools — connect in under 2 minutes
Cline is an autonomous AI coding agent inside VS Code that plans, executes, and iterates on tasks. Wire Langfuse (LLM Tracing & Evals) through the Vinkius and Cline gains direct access to every tool — from data retrieval to workflow automation — without leaving the terminal.
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"langfuse-llm-tracing-evals": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
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About Langfuse (LLM Tracing & Evals) MCP Server
Connect your Langfuse account to any AI agent and take full control of your LLM observability, prompt management, and quality evaluation through natural conversation.
Cline operates autonomously inside VS Code — it reads your codebase, plans a strategy, and executes multi-step tasks including Langfuse (LLM Tracing & Evals) tool calls without waiting for prompts between steps. Connect 10 tools through the Vinkius and Cline can fetch data, generate code, and commit changes in a single autonomous run.
What you can do
- Trace Orchestration — List and retrieve detailed traces of LLM API sessions, exposing latencies, token counts, and exact chained payloads directly from your agent
- Prompt Vault Access — Query actively managed prompt templates and versions to inspect system instructions and expected input variables
- Observation Analysis — Deep-dive into individual spans, events, and generations within a trace to pinpoint failures or performance bottlenecks securely
- Evaluation & Scoring — Attach structured human feedback or automated evaluation metrics to specific traces to monitor model grounding and accuracy
- Usage Metrics — Generate aggregated daily reports on USD costs and average latency to track your AI infrastructure spending in real-time
- Session Monitoring — Extract correlated user sessions to understand multi-turn interaction boundaries and improve long-term agentic workflows
The Langfuse (LLM Tracing & Evals) MCP Server exposes 10 tools through the Vinkius. Connect it to Cline in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Langfuse (LLM Tracing & Evals) to Cline via MCP
Follow these steps to integrate the Langfuse (LLM Tracing & Evals) MCP Server with Cline.
Open Cline MCP Settings
Click the MCP Servers icon in the Cline sidebar panel
Add remote server
Click "Add MCP Server" and paste the configuration above
Enable the server
Toggle the server switch to ON
Start using Langfuse (LLM Tracing & Evals)
Ask Cline: "Using Langfuse (LLM Tracing & Evals), help me..." — 10 tools available
Why Use Cline with the Langfuse (LLM Tracing & Evals) MCP Server
Cline provides unique advantages when paired with Langfuse (LLM Tracing & Evals) through the Model Context Protocol.
Cline operates autonomously — it reads your codebase, plans a strategy, and executes multi-step tasks including MCP tool calls without step-by-step prompts
Runs inside VS Code, so you get MCP tool access alongside your existing extensions, terminal, and version control in a single window
Cline can create, edit, and delete files based on MCP tool responses, enabling end-to-end automation from data retrieval to code generation
Transparent execution: every tool call and file change is shown in Cline's activity log for full visibility and approval before committing
Langfuse (LLM Tracing & Evals) + Cline Use Cases
Practical scenarios where Cline combined with the Langfuse (LLM Tracing & Evals) MCP Server delivers measurable value.
Autonomous feature building: tell Cline to fetch data from Langfuse (LLM Tracing & Evals) and scaffold a complete module with types, handlers, and tests
Codebase refactoring: use Langfuse (LLM Tracing & Evals) tools to validate live data while Cline restructures your code to match updated schemas
Automated testing: Cline fetches real responses from Langfuse (LLM Tracing & Evals) and generates snapshot tests or mocks based on actual payloads
Incident response: query Langfuse (LLM Tracing & Evals) for real-time status and let Cline generate hotfix patches based on the findings
Langfuse (LLM Tracing & Evals) MCP Tools for Cline (10)
These 10 tools become available when you connect Langfuse (LLM Tracing & Evals) to Cline via MCP:
create_observation
Create a new LLM observation (span, event, generation) inside a trace
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
get_daily_metrics
Generate rolled-up USD cost and aggregated latency statistics
get_observation
Retrieve explicit span or generation context within a trace
get_trace
Get complete telemetry and nested graph for a single trace
list_observations
List raw observation objects spanning across traces
list_prompts
Extract actively managed prompt templates and versions
list_scores
List all explicit scores mapping quality or cost algorithms
list_sessions
List high-level user session entities encapsulating multiple traces
list_traces
List all traces tracking LLM API sessions
Example Prompts for Langfuse (LLM Tracing & Evals) in Cline
Ready-to-use prompts you can give your Cline agent to start working with Langfuse (LLM Tracing & Evals) immediately.
"List the last 5 traces in my Langfuse project"
"Show me the instructions for the 'customer-support-v3' prompt"
"What was our total LLM spending for today?"
Troubleshooting Langfuse (LLM Tracing & Evals) MCP Server with Cline
Common issues when connecting Langfuse (LLM Tracing & Evals) to Cline through the Vinkius, and how to resolve them.
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Langfuse (LLM Tracing & Evals) + Cline FAQ
Common questions about integrating Langfuse (LLM Tracing & Evals) MCP Server with Cline.
How does Cline connect to MCP servers?
Can Cline run MCP tools without approval?
Does Cline support multiple MCP servers at once?
Connect Langfuse (LLM Tracing & Evals) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Langfuse (LLM Tracing & Evals) to Cline
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.