"Transcribing Voice Conversations into Structured Meeting Notes" matching MCP servers:

An enhanced MCP server that enables users to interact with NotebookLM while ensuring strict source fidelity and citation accuracy through client-side prompt structuring. It guides Claude to transform user queries into structured prompts that prevent the addition of external knowledge during document analysis.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

Enables AI assistants to read, search, and traverse your reMarkable tablet library, including handwritten notes via OCR, turning it into a second brain.

Integrates Granola.ai meeting intelligence with MCP clients to provide direct access to meeting notes, transcripts, and workspace organization. It allows users to search and retrieve meeting content through natural language by leveraging existing Granola credentials.

MCP server connecting Claude/Cursor to Codex CLI, enabling code analysis via @ file references, multi-turn conversations, sandboxed edits, and structured change mode.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.

Enables AI assistants to read, search, and traverse your entire reMarkable library, including handwritten notes via OCR.

MCP server that connects AI assistants to your reMarkable tablet, enabling reading, searching, and traversing handwritten and typed notes via OCR.

Enables Yelp business search, place details, and full review feeds as structured JSON through a hosted MCP endpoint, with no Yelp Fusion key required.

Standalone MCP server for Obsidian vaults - hybrid search (FTS5 + vector + cross-encoder reranking), images and PDFs in agent-readable form, Kanban-aware tasks (Tasks-plugin + Dataview formats), structured memory with topic recall, fine-grained read/write tools for optimal token efficiency, and link graph support. Run locally, self-host, or one-click deploy for remote access. OAuth 2.1.

Enables AI assistants to read, search, and traverse your reMarkable tablet's library, including handwritten notes via OCR.

Enables MCP clients to search Amazon products, retrieve product details by ASIN, look up seller profiles, and browse seller catalogues as structured JSON across 23 regional Amazon domains.

MCP server for video analysis — extracts transcripts, key frames with OCR, and annotated timelines from video URLs. Supports Loom and direct video files (.mp4, .webm). Zero auth required.

An MCP server that turns AI assistants into competent Festo/CODESYS PLC engineers by grounding them in curated, manufacturer-accurate knowledge and forcing every artifact through a machine-checked validation pipeline for CODESYS import.

Enables MCP clients to search Walmart products by keyword or category, retrieve product details including the buy box and other sellers, and page through customer reviews with filters, all as structured JSON without a Walmart developer account.

Provides coding agents with visibility into test health through tools for flaky test detection, test quality linting, and LLM evaluation harness, enabling them to triage failures, review test quality, and check prompt changes for regressions.

Provides enterprise architecture knowledge tools that ground agents in curated patterns, enabling translation of messy enterprise asks into realistic architecture recommendations, platform selection, risk checks, and brand context retrieval.

Provides a read-only MCP interface to the Santismm Knowledge Platform, offering tools to retrieve curated content on engineering, AI patterns, architectures, governance, and agent taxonomy with structured output in English, Spanish, and Portuguese.

MCP server that injects verified FTC documentation and code examples into AI assistants, enabling teams to write correct, competition-ready Java robot code through natural language.