What is the key difference between Langfuse Mcp Java and OnchainAI?

Langfuse Mcp Java belongs to the Monitoring category with local stdio execution, while OnchainAI belongs to the Monitoring category with local stdio execution.

How do I install Langfuse Mcp Java or OnchainAI in Claude Desktop or Cursor?

Copy the mcpServers JSON configuration snippet provided on this page into your claude_desktop_config.json or ~/.cursor/mcp.json file and restart your AI client.

Are Langfuse Mcp Java and OnchainAI free or paid?

Langfuse Mcp Java operates under a BYOK (Pay Provider Direct) model (API Key required). OnchainAI operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Langfuse Mcp Java lists 55 tools with 3 views and 3 GitHub stars. OnchainAI lists 11 tools with 0 views and 1 GitHub stars.

Can I use both Langfuse Mcp Java and OnchainAI together in the same MCP host?

Yes! MCP hosts like Claude Desktop, Cursor, Windsurf, Cline, and VS Code support configuring multiple servers under the mcpServers object simultaneously.

How do I install Langfuse Mcp Java or OnchainAI in Claude Desktop, Cursor, or Windsurf?

Both servers follow the standard Model Context Protocol configuration format. Simply copy the JSON block from the configuration section above and paste it into your AI client's mcpServers configuration object (for instance in claude_desktop_config.json or ~/.cursor/mcp.json ), then completely restart or refresh the application.

Are Langfuse Mcp Java and OnchainAI free to use, or do they require API keys?

Langfuse Mcp Java is listed under a BYOK (Pay Provider Direct) model with API Key required . OnchainAI operates under a Free / Open Source model with No auth required . If environment variables are required (such as API keys), be sure to define them under the env key in your MCP client's configuration file.

Can I run both Langfuse Mcp Java and OnchainAI at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both log-logn-langfuse-mcp-java and onchainai as distinct keys inside the single mcpServers object in your configuration file. Your AI assistant will automatically select and call the appropriate tool from either server during chat sessions.

Which MCP server has higher directory engagement and quality ratings?

On AllMCPs, Langfuse Mcp Java has a Quality Score of 60 /100 ( Good ) with 3 views, 0 installs, and 3 GitHub stars. OnchainAI holds a Quality Score of 52 /100 ( Good ) with 0 views, 0 installs, and 1 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Langfuse Mcp Java vs OnchainAI

In-depth architectural comparison of the Langfuse Mcp Java and OnchainAI MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.

At a Glance & Executive Verdict

Langfuse Mcp Java

Monitoring · Local stdio

Quality: 60/100 (Good) | Auth: API Key required

OnchainAI

Monitoring · Local stdio

Quality: 52/100 (Good) | Auth: No auth required

Verdict Summary: Choose Langfuse Mcp Java if you need specialized Monitoring tools running via a local process. Choose OnchainAI if your workspace requires Monitoring integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose Langfuse Mcp Java when:

You need dedicated capabilities in the Monitoring domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: API Key required (BYOK (Pay Provider Direct)).
You have access to required keys: LANGFUSE_PUBLIC_KEY, LANGFUSE_SECRET_KEY, LANGFUSE_HOST, LANGFUSE_TIMEOUT.
Primary tools included: fetch_traces, fetch_trace, find_exceptions.

Explore Langfuse Mcp Java Details

Choose OnchainAI when:

You need dedicated capabilities in the Monitoring domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: search_tools, get_tool_detail, get_install_guide.

Explore OnchainAI Details

Feature & Specification Comparison

Specification	Langfuse Mcp Java log-logn Monitoring	O OnchainAI Monitoring
Summary	Query Langfuse traces, debug exceptions, analyze sessions, scores, datasets, schema, observations and manage prompts. Full observability toolkit for LLM applications. (https://github.com/langfuse/langfuse)	Crypto tool directory MCP for AI agents — discover MCP/CLI/SDK/API/x402 tools with trust metadata.
Category & Scope	Monitoring	Monitoring

Tools & Capabilities Breakdown

Langfuse Mcp Java Tools (55)

fetch_traces

Paginated list of traces. Filter by `userId`, `name`, `sessionId`, `tags`, `fromTimestamp`, `toTimestamp`.

fetch_trace

Full detail of a single trace including nested observations, input/output, metadata, latency, and token usage. Requires `traceId`.

find_exceptions

Traces whose `level` equals `ERROR`. Supports time range and pagination.

find_exceptions_in_file

Error-level traces whose metadata contains a given file name substring. Requires `fileName`.

get_exception_details

Full detail of a single error trace. Requires `traceId`.

Ready-to-Paste Client Configurations

Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).

Langfuse Mcp Java Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "log-logn-langfuse-mcp-java": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/inspector"
      ],
      "env": {
        "LANGFUSE_PUBLIC_KEY": "YOUR_LANGFUSE_PUBLIC_KEY_HERE",
        "LANGFUSE_SECRET_KEY": "YOUR_LANGFUSE_SECRET_KEY_HERE",
        "LANGFUSE_HOST": "YOUR_LANGFUSE_HOST_HERE",
        "LANGFUSE_TIMEOUT": "YOUR_LANGFUSE_TIMEOUT_HERE"
      }
    }
  }
}

OnchainAI Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "onchainai": {
      "command": "npx",
      "args": [
        "-y",
        "add-mcp"
      ]
    }
  }
}

Frequently Asked Questions

Langfuse Mcp Java is categorized under Monitoring and uses a local stdio subprocess. In contrast, OnchainAI belongs to Monitoring using local stdio subprocess. Select Langfuse Mcp Java when you need capabilities focused on monitoring and OnchainAI when you require tools for monitoring.

More alternatives to Langfuse Mcp Java More alternatives to OnchainAI Monitoring category hub