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DrishtantKaushal

Langfuse MCP Server

by DrishtantKaushal
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Python
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    TDQS

    B3.1/5.0

    Scored across 58 tools

    Disambiguation4/5

    Most tools target distinct resource+action pairs, and descriptions contain helpful cross-references (e.g., fetch_traces vs fetch_trace vs search_trace_content). However, fetch_scores and list_scores_v2 both list scores and differ only by API version, and the error-related tools (find_exceptions, get_error_count, get_exception_details) have somewhat fuzzy boundaries that descriptions must work hard to clarify.

    Naming Consistency3/5

    Nearly all names follow a verb_noun pattern with descriptive nouns, but the retrieval verbs are used inconsistently: get_prompt/get_dataset/get_model vs fetch_trace/fetch_observations/fetch_sessions for the same kind of operation, and list_scores_v2 sits alongside fetch_scores. The mixed get/fetch/list convention creates avoidable confusion.

    Tool Count2/5

    58 tools is far above the comfortable range and will strain agent tool-selection accuracy and context budgets. While Langfuse is a broad platform, this surface spans CRUD, analytics, and management concerns that could be split into separate servers or consolidated (e.g., the 10+ analytics tools repeatedly fetch and aggregate traces in overlapping ways).

    Completeness4/5

    The surface covers the core Langfuse domains well: traces, sessions, observations, scores (read/write), prompts, datasets, comments, models, and annotation queues, plus a robust analytics layer. Minor gaps exist (no delete for comments/prompts/datasets, no model creation), but these align with Langfuse API constraints and don't create dead ends for common workflows.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources