Skip to main content
Glama
nipunkhanderia

golden-dataset-mcp

by nipunkhanderia
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to golden-dataset-mcp

No user-submitted related servers found.

    Related Servers

    • evalsmith-mcp

      diegoperezg7
      A
      license
      A
      quality
      A
      maintenance
      Enables MCP clients to score retrieval quality with recall, precision, nDCG, hit rate and MRR, compare 2-3 configurations with seeded paired-bootstrap confidence intervals, audit agent tool calls against expected traces, and detect prompt regressions against golden sets. It also generates Markdown, JSON or JUnit reports with pass/fail gates, all deterministically and offline without paid API keys.
      6
      308 npm
      1
      MIT

    • IndexFoundry MCP

      Mnehmos
      F
      license
      Not graded
      quality
      B
      maintenance
      Creates deterministic, auditable vector databases from any content source with deployable RAG applications. Supports multiple embedding providers and vector databases with fine-grained pipeline control or project-based workflows.
      14 npm
      6
      -

    • rag-mcp

      NextLevelManagementAdvisors
      A
      license
      A
      quality
      C
      maintenance
      Enables ingestion and semantic search over text documents using PostgreSQL + pgvector and OpenAI-compatible embeddings, allowing any LLM agent to retrieve relevant chunks for grounded answers.
      4
      AGPL 3.0

    • AgentOps EvalBench MCP

      AbhinavVarma02
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables LLM evaluation and observability by uploading documents, building test sets, running RAG pipelines, and automatically scoring answers for groundedness, hallucination risk, retrieval quality, latency, and cost, with tools exposed to MCP-compatible clients.
      1
      MIT
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.9/5.0

    Scored across 9 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: init, add, delete, update, list, commit, status, diff, and evaluate. No two tools overlap in functionality.

    Naming Consistency5/5

    All tool names follow the verb_noun pattern in snake_case, e.g., add_entry, commit_version, list_entries. Consistent and predictable.

    Tool Count5/5

    9 tools is well-scoped for a version-controlled golden dataset server. It covers all essential operations without being bloated or sparse.

    Completeness4/5

    The tool surface covers init, CRUD for working tree, versioning, listing, status, diff, and evaluation. Minor gap: no dedicated get-single-entry tool, but list_entries likely returns full entries.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources