Skip to main content
Glama
Manas-maker

shap-mcp

by Manas-maker
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Related Servers

Alternatives to shap-mcp

No user-submitted related servers found.

    Related Servers

    • my-mcp-server2

      kcbabo
      F
      license
      Not graded
      quality
      D
      maintenance
      A Model Context Protocol server built with FastMCP that features dynamic tool loading and modular management via a dedicated tool directory. It supports both stdio and HTTP transport modes, enabling efficient development and deployment of custom MCP tools.
      -

    • anthropic_skill

      williamchek
      F
      license
      Not graded
      quality
      D
      maintenance
      A robust, lightweight Model Context Protocol (MCP) server designed to empower your AI Agents with context-awareness, safe execution sandboxes, and dedicated thought logs.
      -

    • openlocal

      DevXV3
      A
      license
      Not graded
      quality
      C
      maintenance
      A zero-dependency MCP and agent tool server for small local models that provides a measured, deterministic tool-calling interface with file, web, shell, and calculation tools.
      MIT

    • MCP Demo

      VictorC55
      F
      license
      Not graded
      quality
      C
      maintenance
      A model-agnostic MCP server exposing example tools (add1, multiply2, greet) for learning purposes, working with any LLM through stdio transport.
      -
    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

    A3.5/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: model loading, SHAP computation, global importance, local explanation, interaction values, and plotting. There is no overlap or ambiguity in what each tool does, so an agent can reliably select the correct one for a given task.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with lowercase and underscores (load_model, run_analysis, get_feature_importance, etc.). The verbs vary but are semantically appropriate, and the naming style is uniform across the set, making the API predictable.

    Tool Count5/5

    Six tools provide a well-scoped surface for SHAP analysis. This is an appropriate size that covers the core workflow (load, analyze, query results, plot) without redundancy or unnecessary bloat. Each tool earns its place in the server.

    Completeness5/5

    The tool surface covers the full lifecycle of a SHAP analysis: loading a model, running the explainer, retrieving global and local explanations, getting interactions, and generating visualizations. There are no obvious gaps that would block an agent from completing typical analysis tasks.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources