"How to create a unit test for a project" matching MCP servers:

Fetches category data from a Q&A service API and returns a markdown summary grouped by category.

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

Enables LLM clients to search a firm's precedent vault and draft grounded contract clauses, legal memos, and document summaries.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

Enables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

A local-first Codex plugin that bundles an MCP server to safely interact with Mattermost, enabling channel/thread summarization, conversation search, and reviewed post publishing via the Mattermost REST API.

The Documentize MCP server exposes all document processing capabilities as tools for AI agents and LLM clients — convert, merge, extract, sign, and more, directly from Claude Desktop, VS Code Copilot, Cursor, or any MCP-compatible host.

Enables fetching, searching, and summarizing YouTube video transcripts with multi-language support.

This MCP server enables AI assistants to perform calculations, fetch live weather, manage in-memory notes, access system info and note resources, and use reusable code review and summarization prompts.

Summarizes Slack activity and GitLab merge requests with OpenAI to help generate daily standups, weekly reports, or quarterly check-ins.

A Python-based MCP server adapted from the n8n_agent project that implements a note storage and summarization system. It enables users to create, retrieve, and summarize notes through the Model Context Protocol.

Enables Claude to read, rewrite, generate, and summarize LibreOffice Writer documents with preview-then-apply editing through MCP tools, authenticating via Claude Code login.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

A small MCP server that gives agents rich context about a YouTube video — its transcript, jump-to-the-moment deep links, metadata, and most-replayed moments — so they can answer questions, summarize, pull quotes, or surface highlights.

MCP server for evidence-based bullet point summarization guidance. Validates and improves bullet lists using scientifically-validated principles from cognitive psychology and UX research.

tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.

Measures AI-detection risk in text and provides a line-by-line rewrite plan to lower the score.

Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.