Skip to main content
Glama
lea-blum

Headroom Mini

by lea-blum
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Related Servers

Alternatives to Headroom Mini

No user-submitted related servers found.

    Related Servers

    • tokencompress

      jiawei686
      A
      license
      Not graded
      quality
      C
      maintenance
      A local, zero-cloud MCP server for token and text compression. It provides tools to compress, auto-compress, measure, and decompress text using offline rules, lossless gzip packing, or a local Ollama semantic model.
      1
      MIT

    • Compendium

      hocestnonsatis
      A
      license
      Not graded
      quality
      A
      maintenance
      MCP server that minimizes LLM token usage by compressing, summarizing, filtering, chunk-referencing, and pruning large context before it reaches the model, with heuristic or local-SLM smart actions, caching, and token counting.
      21 npm
      MIT

    • slimctx-token-optimizer

      omkar9854
      A
      license
      A
      quality
      A
      maintenance
      Provides reversible context compression for AI agents, reducing token usage while preserving the ability to retrieve original content, and serves as an MCP server for integration with tools like GitHub Copilot and Claude Code.
      3
      1
      Apache 2.0
    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

    B3.3/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool targets a distinct operation: compression of code vs JSON, redaction, hydration, and prompt optimization. There is no functional overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., compress_code, redact_content), making them predictable for an agent.

    Tool Count5/5

    With 5 tools, the server is well-scoped for content manipulation tasks. Each tool serves a clear purpose without unnecessary redundancy.

    Completeness3/5

    The set covers compression, redaction, hydration, and prompt optimization, but lacks a decompress tool for JSON minification and potentially other common formats, leaving a minor gap.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources