Summarization Functions
@Braffolk
Summarization Functions について
Provides summarised output from various actions that could otherwise eat up tokens and cause crashes for AI agents
基本情報
設定
ツール
ツールは検出されませんでした
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
What is Summarization Functions?
An MCP server that provides intelligent text summarization for AI agents, primarily developed to enhance context window management and prevent overflow. It integrates with the Model Context Protocol and supports multiple AI providers (Anthropic, OpenAI, OpenAI-compatible, Google).
How to use Summarization Functions?
Install via npm i mcp-summarization-functions, then add the server to your MCP configuration file with required environment variables (PROVIDER and API_KEY). Use tools like summarize_command, summarize_files, summarize_directory, summarize_text, and get_full_content.
Key features of Summarization Functions
- Command output summarization with execution.
- File content analysis with technical accuracy.
- Directory structure overview with recursion.
- Flexible model support across providers.
- AI agent context optimization with caching.
Use cases of Summarization Functions
- Summarizing large command outputs to prevent AI agent context overflow.
- Analyzing file contents focused on security, API surface, or errors.
- Getting quick overviews of complex directory structures.
- Summarizing arbitrary text like logs, errors, or API responses.
FAQ from Summarization Functions
What AI providers are supported?
Anthropic (Claude), OpenAI (GPT), OpenAI‑compatible (e.g., Azure), and Google (Gemini).
How is it used with AI agents?
Include the provided “CONTEXT MANAGEMENT” prompt in agent instructions to mandate summarization for all large outputs (commands, files, directories, etc.).
What tools does the server expose?
summarize_command, summarize_files, summarize_directory, summarize_text, and get_full_content.
What environment variables are required?
PROVIDER (e.g., ANTHROPIC) and API_KEY. Optional: MODEL_ID, PROVIDER_BASE_URL, MAX_TOKENS, SUMMARIZATION_CHAR_THRESHOLD, SUMMARIZATION_CACHE_MAX_AGE, and MCP_WORKING_DIR.
Is there a caching mechanism?
Yes; summarized content is cached with a default maximum age of 1 hour (SUMMARIZATION_CACHE_MAX_AGE). Full content is stored for later retrieval via get_full_content.
「その他」の他のコンテンツ
FastMCP v2 🚀
jlowin🚀 The fast, Pythonic way to build MCP servers and clients.
MCP Toolbox for Databases
googleapisMCP Toolbox for Databases is an open source MCP server for databases.
Activepieces
activepiecesAI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
Reactive Resume
amruthpillaiA one-of-a-kind resume builder that keeps your privacy in mind. Completely secure, customizable, portable, open-source and free forever. Try it out today!
MCP Go 🚀
mark3labsA Go implementation of the Model Context Protocol (MCP), enabling seamless integration between LLM applications and external data sources and tools.
コメント