Skip to main content
Glama
yangsong7

infra-advisor-mcp

by yangsong7
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to infra-advisor-mcp

No user-submitted related servers found.

    Related Servers

    • chimeraforge

      Sahil170595
      A
      license
      A
      quality
      A
      maintenance
      LLM deployment planner: given a model and a GPU, answers will it fit, will it hit your SLO, and what will it cost. Sizes VRAM and KV-cache from the model's real architecture, and labels every number measured, estimated, or unknown.
      5
      735 PyPI
      2
      MIT
    • OptimToken MCP by OptimNow

      OptimToken MCPofficial

      OptimNow
      A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI assistants to fetch live, dated prices for LLM models and cloud compute instances across providers, compare and recommend models, and estimate monthly costs based on workload-specific token shapes and constraints.
      MIT

    • atom-mcp-server

      A7OM-AI
      A
      license
      A
      quality
      D
      maintenance
      Global price benchmarking for AI inference across 2,600+ SKUs from 47 vendors. Query live pricing, market indexes, and model specs via 8 tools. Free tier available.
      8
      78 npm
      MIT

    • ai-cost-calculator-api

      lazymac2x
      F
      license
      Not graded
      quality
      D
      maintenance
      Enables AI cost calculation, comparison, and optimization across major providers like Anthropic, OpenAI, Google, Meta, and Mistral. Supports cost estimation, budget-aware model finding, and token estimation through a simple API and MCP integration.
      -
    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

    A4.2/5.0

    Scored across 12 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose, from task analysis to cost estimation and report generation. No overlapping functionalities; descriptions clearly differentiate between inference cost, maintenance, training, and comparison tools.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (e.g., analyze_task, estimate_inference_cost, generate_full_report). No mixing of conventions or vague verbs.

    Tool Count5/5

    With 12 tools, the server covers the full lifecycle of infrastructure planning without being bloated. Each tool serves a necessary function, and the count is ideal for the domain.

    Completeness5/5

    The tool set comprehensively addresses the domain: task analysis, model recommendation, inference/training/maintenance cost estimation, TCO comparison, data freshness checks, and report generation/saving. No obvious gaps for the stated purpose.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources