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ericortiz604

Langfuse MCP Server

by ericortiz604
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Python
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    • Langfuse MCP Server

      robertmatuda
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      license
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      quality
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      maintenance
      Enables AI agents to query and debug trace, session, observation, and exception data, analyze latency and metrics, and manage prompts, datasets, and annotation queues. Supports selective tool-group loading, compact or file-dump output, and a read-only mode for safer access.
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    • Langfuse MCP Server

      pablokrylov766
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      license
      Not graded
      quality
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      maintenance
      Enables AI agents and developers to query traces, observations, sessions, and exceptions, plus prompts, datasets, annotation queues, scores, and aggregated metrics, for local debugging and observability from any MCP client. Supports selective tool-group loading to cut token overhead and a read-only mode that disables all write operations.
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    • Langfuse MCP Server

      HasanFontana78403
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      license
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      quality
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      Enables AI agents and MCP clients such as Claude Code, Codex, and Cursor to query and debug trace, session, and exception data locally, including route-decision analysis, metrics aggregation, prompts, datasets, and annotation queues. Offers selective tool loading and a read-only mode to control token overhead and write access.
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    • Langfuse MCP Server

      Catherineh0509
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      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents and developers to query Langfuse telemetry locally, fetching traces, sessions, observations, and exceptions, inspecting route decisions, and running metrics, prompt, dataset, and annotation-queue operations. Supports selective tool-group loading and a read-only mode for token-efficient debugging from Claude Code, Codex, Cursor, or any MCP client.
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    • Langfuse MCP Server

      Jaehyunr9433
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables MCP clients such as Claude Code, Codex, and Cursor to debug failing traces, sessions, and exceptions, inspect route decisions, prompts, datasets, and metrics, and control token overhead via compact output, file dumps, and selective tool loading. It supports local stdio or HTTP deployment with optional read-only mode for safer observability workflows.
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