Skylos vs Langfuse MCP

Choosing between Skylos and Langfuse MCP? Both are monitoring MCP servers, but they lean into different workflows. This page focuses on where each one is actually stronger, not just raw counts.

Choose Skylos for

Cleaning up legacy codebases by identifying and removing unused functions.

Choose Langfuse MCP for

Debugging production LLM application errors by inspecting trace logs.

Skylos

344by duriantacostdio

Find dead code, secrets, and exploitable flows in Python, TypeScript, and Go.

Best for Cleaning up legacy codebases by identifying and removing unused functions.

Skylos: Dead Code and Security PR Gate for Modern Codebases Find dead code, secrets, and exploitable flows in Python, TypeScript, and Go. Add a pull request gate in minutes.

📖 Website · Documentation · Blog · VS Code Extension.

What it does

  • Detects dead code in Python, TypeScript, and Go projects
  • Identifies security vulnerabilities like SQLi and hardcoded secrets
  • Framework-aware analysis for FastAPI, Django, pytest, and Next.js
  • Provides AI-powered analysis and remediation suggestions
  • Supports CI/CD integration with quality gates and PR annotations

Available tools (2)

scanScans the codebase for dead code, security vulnerabilities, and quality issues.
defendPerforms AI defense checks for Python LLM integrations.
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vs

Langfuse MCP

66by avivsinaistdio

MCP server for Langfuse observability and LLM application management.

Best for Debugging production LLM application errors by inspecting trace logs.

Model Context Protocol server for Langfuse observability. Query traces, debug errors, analyze sessions, manage prompts.

Why langfuse-mcp?

What it does

  • Full observability toolkit including traces, observations, and sessions.
  • Comprehensive exception tracking and debugging capabilities.
  • Full management of LLM prompts and datasets.
  • Selective tool loading to reduce token overhead.
  • Read-only mode for secure, restricted access.

Available tools (5)

fetch_tracesRetrieve a list of traces from Langfuse.
fetch_traceGet detailed information for a specific trace.
find_exceptionsSearch for exceptions within Langfuse logs.
list_promptsList all available prompts in the Langfuse project.
create_dataset_itemCreate or update an item within a dataset.

Setup requirements

Requires 4 environment variables: LANGFUSE_PUBLIC_KEY, LANGFUSE_SECRET_KEY, LANGFUSE_HOST, LANGFUSE_MCP_READ_ONLY. Available via Claude Code and Docker.

View Langfuse MCP details

Biggest differences

CompareSkylosLangfuse MCP
Best forCleaning up legacy codebases by identifying and removing unused functions.Debugging production LLM application errors by inspecting trace logs.
StandoutDetects dead code in Python, TypeScript, and Go projects.Full observability toolkit including traces, observations, and sessions.
SetupPip, stdio transport.Claude Code or Docker, needs 4 env vars, stdio transport.
Transportstdiostdio
Community344 GitHub stars66 GitHub stars

Bottom line

Pick Skylos if...

Cleaning up legacy codebases by identifying and removing unused functions. Detects dead code in Python, TypeScript, and Go projects. Pip, stdio transport.

Pick Langfuse MCP if...

Debugging production LLM application errors by inspecting trace logs. Full observability toolkit including traces, observations, and sessions. Claude Code or Docker, needs 4 env vars, stdio transport.

The real split here is workflow fit, not raw counts. Skylos: Cleaning up legacy codebases by identifying and removing unused functions. Langfuse MCP: Debugging production LLM application errors by inspecting trace logs. Skylos also has the larger public footprint (344 vs 66 stars).

Keep the comparison logic in memory

Once you pick a server, keep the decision notes, setup rules, and docs in Conare so your agent can apply them again without re-explaining.

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How to set up Skylos → How to set up Langfuse MCP →