Skip to main content
Glama
Sign In
nishide-dev

ML Research MCP

by nishide-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Related Servers

Alternatives to ML Research MCP

No user-submitted related servers found.

    Related Servers

    • BioVis-MCP

      muslus
      A
      license
      Not graded
      quality
      D
      maintenance
      Enables AI assistants to generate publication-quality bioinformatics visualizations (volcano plots, PCA, heatmaps, etc.) directly from raw biological data.
      MIT

    • Viz MCP Server

      ceeyang-ai
      A
      license
      A
      quality
      C
      maintenance
      Enables AI agents to create data visualizations like bar charts, line charts, pie charts, scatter plots, and histograms, returning inline SVG or PNG files.
      5
      MIT

    • Charta MCP

      mortenator
      A
      license
      Not graded
      quality
      Not graded
      maintenance
      Enables AI agents to generate beautiful, presentation-ready charts (SVG + PNG) with zero setup, supporting various chart types and styling options.
      25 npm
      MIT

    • d3-visualization-mcp

      waqasdaar
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to ingest and link datasets, plan and render interactive D3.js visualizations and dashboards, validate and refine outputs, and export standalone HTML, SVG, PNG, PDF, JSON, or CSV artifacts from natural-language requests.
      MIT

    • SlickFast

      SlickFast
      A
      license
      Not graded
      quality
      B
      maintenance
      Deterministic chart engine for AI agents. A small JSON spec renders locally to PNG or SVG with no headless browser. 47 chart types, tiled dashboards and 8 scientific plots (Kaplan-Meier, volcano, Bland-Altman, Q-Q).
      1
      AGPL 3.0
    Deploy Server
    Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

    TDQS

    A4.3/5.0

    Scored across 9 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose corresponding to a specific type of plot visualization. The descriptions clearly differentiate between bar plots, box plots, contour plots, heatmaps, histograms, line plots, pseudocolor plots, scatter plots, and violin plots. There is no functional overlap or ambiguity between these visualization types.

    Naming Consistency5/5

    All tool names follow a perfect 'plot_' prefix pattern with descriptive suffixes indicating the plot type. The naming is completely consistent across all nine tools, using snake_case uniformly without any deviations or mixed conventions.

    Tool Count5/5

    Nine tools is an appropriate number for a visualization-focused ML research server. Each tool represents a distinct, commonly used plot type in data analysis and research, making the set well-scoped without being overwhelming or insufficient for the domain.

    Completeness4/5

    The tool set covers most essential plot types for ML research visualization, including categorical, distribution, correlation, and relationship plots. Minor gaps might include specialized plots like 3D surface plots or network graphs, but the core visualization needs are well-covered for typical research workflows.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources