Skip to main content
Glama
malaksedarous

Context Optimizer MCP Server

by malaksedarous
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Related Servers

Alternatives to Context Optimizer MCP Server

No user-submitted related servers found.

    Related Servers

    • Ambiance MCP Server

      sbarron
      A
      license
      A
      quality
      D
      maintenance
      Provides intelligent code context and analysis through semantic compression, AST parsing, and multi-language support. Offers 60-80% token reduction while enabling AI assistants to understand codebases through local analysis, OpenAI-enhanced insights, and GitHub repository integration.
      6
      10 npm
      3
      MIT

    • Semantic Cache MCP

      CoderDayton
      A
      license
      A
      quality
      A
      maintenance
      Reduces token consumption by over 80% through intelligent file caching, returning only diffs for modified files and suppressing unchanged content. It features a suite of 12 tools for semantic search, batch reading, and efficient file editing to optimize LLM interactions with large codebases.
      14
      2
      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

    A3.7/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool targets a distinct source and action: file analysis, quick web research, deep web research, terminal command follow-up, and terminal execution with extraction. While researchTopic and deepResearch are related, their descriptions clearly separate quick versus exhaustive research, preventing mis-selection.

    Naming Consistency3/5

    Names are readable and mostly camelCase, but follow different patterns: askAboutFile and askFollowUp use 'ask' + phrase, researchTopic is verb+noun, deepResearch is an adjective-noun phrase, and runAndExtract is verb+verb. The mixed conventions are still predictable in context but lack a consistent verb_noun structure.

    Tool Count5/5

    Five tools is well-scoped for a context optimization server. Each tool fills a clear niche—file extraction, quick research, deep research, command execution extraction, and follow-up—without redundancy or clutter.

    Completeness4/5

    The surface covers the main context-gathering needs: files, web research, and terminal output. A minor gap is that askFollowUp only attaches to runAndExtract, leaving no follow-up mechanism for askAboutFile or research results, but agents can still work around this.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources