"MCP server for transaction description enrichment using LLMs" matching MCP servers:

An MCP server that exposes the llms.txt file and its referenced local or external resources from a project root to provide context for AI models. It automatically parses documentation links and URLs to make them accessible as additional MCP resources.

Enables coding agents to establish exact-release library identity, search provenance-tracked API, docs, example, source, and release evidence, compare releases, and test proposed invocations in isolated capsules for Rust and Python dependency environments.

MCP server for SecretiveShell/Awesome-llms-txt. Add documentation directly into your conversation via MCP resources.

Enables agents to discover the llms.txt index covering any site, fetch its linked documentation pages as markdown, and search across parsed indexes by section heading, link title, and notes.

A generic MCP (Model Context Protocol) server for any Hugo blog, deployed on Cloudflare Workers. It reads your blog's llms.txt and llms-full.txt files and exposes them as structured tools that AI assistants can query to understand your content.

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.

Optimizes EDT MCP tool descriptions by replacing verbose documentation with concise summaries stored in SQLite, reducing context usage while allowing on-demand retrieval of full tool guides.

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

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.

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.

Enables MCP host applications to retrieve and process structured documentation from user-defined llms.txt files. It provides tools to fetch specific URLs and audit the documentation context returned to the LLM.

An MCP server that provides tools to load and fetch documentation from any llms.txt source, giving users full control over context retrieval for LLMs in IDE agents and applications.

Enables AI assistants to coordinate real estate transactions, extract contract data, track deadlines, search case law, and draft motions via PrimaCoda's platform.

Provides controlled access to llms.txt documentation files through MCP tools, allowing AI assistants to fetch and read documentation from user-approved domains with full audit visibility of tool calls and context retrieval.

Provides a user-defined list of llms.txt files and a fetch_docs tool to read documentation URLs from those files, enabling controlled and auditable documentation retrieval for MCP host applications.

A read-only MCP server providing curated Qdrant documentation for LLMs, enabling retrieval of the latest and most accurate documentation.

An MCP server that enables users to fetch and audit documentation from user-defined llms.txt index files. It provides tools to list documentation sources and retrieve content from specific URLs with built-in domain access controls for secure context retrieval.

An open-source MCP server that provides applications like Cursor, Windsurf, and Claude with access to llms.txt documentation files, allowing users to control and audit context retrieval.

An MCP server that retrieves and cleans official documentation for popular AI/Python libraries via web search and LLM processing, exposing a get_docs tool.

Enables AI clients to search live documentation for popular developer libraries and return clean, source-cited summaries via a RAG pipeline.