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⇱ Methods to reduce API call frequency | Glama

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Methods to reduce API call frequency

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  • Why this server?

    该服务器通过有效地缓存数据来显式减少令牌消耗，这直接有助于减少对外部服务的API调用次数。

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    A Model Context Protocol server that reduces token consumption by efficiently caching data between language model interactions, automatically storing and retrieving information to minimize redundant token usage.
    Last updated
    4
    25

  • Why this server?

    该工具箱提供了缓存、批处理操作和速率限制功能，这些都是直接减少和管理API调用次数的机制。

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    A collection of tools that enhance MCP-based workflows with caching, retry logic, batch operations, and rate limiting capabilities.
    Last updated
    7
    2
    MIT

  • Why this server?

    该服务器专门用于将多个MCP工具调用批量处理为一个请求，从而显著减少令牌使用和网络开销（即API调用次数）。

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    A simple aggregator server that allows batching multiple MCP tool calls into a single request, reducing token usage and network overhead for AI agents.
    Last updated
    58

  • Why this server?

    该工具通过允许用户精确过滤API响应中的数据，最多可减少99%的令牌使用量，从而避免获取不必要的完整数据，有效减少API调用和数据传输。

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    Enables efficient extraction of specific data from JSON APIs using JSONPath patterns, reducing token usage by up to 99% compared to fetching entire responses. Supports single and batch operations for both JSON extraction and raw text retrieval from URLs.
    Last updated
    4
    3

  • Why this server?

    该服务器旨在提供快速、节省令牌的访问方式，用于处理大型文档，这有助于避免重复加载大量数据，从而减少API调用。

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    Enables fast, token-efficient access to large documentation files in llms.txt format through semantic search. Solves token limit issues by searching first and retrieving only relevant sections instead of dumping entire documentation.
    Last updated
    3
    MIT

  • Why this server?

    该服务器通过优化代码上下文和引用来减少AI助手的令牌使用量，从而降低在代码分析过程中进行冗余查询或API调用的需求。

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    Extracts minimal, relevant code context from multiple programming languages while analyzing diffs and optimizing imports to reduce token usage for AI assistants. Supports TypeScript/JavaScript, Python, Go, and Rust with token-aware caching.
    Last updated
    7
    6
    1
    MIT

  • Why this server?

    该服务器通过语义压缩和AST解析，旨在实现60-80%的令牌减少，这直接转化为显著降低每次操作的API成本和调用次数。

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    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.
    Last updated
    6
    13
    3
    MIT

  • Why this server?

    通过缓存数据来优化令牌使用，并提供持久化的记忆功能，可以避免在重复查询相同信息时再次调用API。

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    A Model Context Protocol (MCP) server that optimizes token usage by caching data during language model interactions, compatible with any language model and MCP client.
    Last updated
    4
    2

  • Why this server?

    作为一个代理和聚合器，它有助于集中管理多个MCP服务器的调用，并能减少发送给单个服务器的冗余请求，从而降低整体API调用次数。

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    A flexible proxy that enables discovery and execution of tools across multiple Model Context Protocol (MCP) servers and JavaScript functions, reducing context size even when dealing with hundreds of tools.
    Last updated
    5
    11
    ISC