"A search for information about refining prompts" matching MCP servers:

A simple MCP server for utilizing prompts defined in YAML files.

Enables extracting explicitly stated contract metadata, clauses, and obligations from user-supplied contract text without storing or modifying the data.

Enables MCP-compatible agents to retrieve Chinese expert documents, prompt examples, and task skeletons before writing Chinese prompts.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

Model Context Protocol server exposing system prompt files and summaries.

Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.

MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.

Enables agents to search, analyze, and explore arXiv academic papers with advanced multi-field search, author lookup, category browsing, citation extraction, and bibliography export.

Search Vascue's public healthcare-operations documentation: AI front desk for clinics, provider-side insurance claims automation, Cliniko integration, security. Public content only.

High-performance code understanding toolkit that enables batch reading of multiple files with dependency context, structural outline extraction with Java annotation awareness, and precise location of classes/methods across large codebases.

Provides 14 enhanced intelligent search tools for both international platforms (GitHub, StackOverflow, NPM, etc.) and Chinese platforms (CSDN, Juejin, WeChat docs, etc.). Each tool includes smart URL generation, search tips, and related suggestions for comprehensive technical research.

Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.

Enables searching documentation from GitHub repositories and web pages via MCP tools, with in-memory indexing and caching for fast retrieval.

MCP server for Yandex Wiki with full-text search. Read and write pages, comments, attachments, and dynamic tables (grids); optional server-side read-only mode for agents. Docker-ready.

Live, ranked search across any number of llms.txt documentation sites - Strands, Kiro, the AWS guides, and whatever you add at runtime.

Provides AI-powered search and documentation tools using Google Vertex AI or Gemini API with real-time web search grounding, enabling technical queries, code analysis, documentation retrieval, and architecture recommendations to overcome LLM knowledge gaps.

Provides AI assistants with locally bundled tools to explore NIST OSCAL models, retrieve schemas, list community resources, and generate valid OSCAL templates for governance, risk, and compliance workflows.

Enables AI agents to subscribe to a deterministic daily ethics feed drawn from a four-module curriculum and retrieve read-only tools, resources, and reflection prompts covering principles, case studies, and codes of conduct.

Enables AI coding assistants to perform real-time web searches for technical documentation and deep-fetch web pages, returning clean structured results. It supports integration with MCP clients such as Cursor, Claude, and CodeBuddy.

Enables searching and retrieving documentation files from a local docs folder using a search tool and dynamic resource URIs.