"A guide to video editing" matching MCP servers:

Enables persistent, auditable business operations state by storing knowledge, evidence, decisions, tasks, execution receipts, and review results in a local SQLite database, so different sessions can continue the same project.

Self-hosted video intelligence pipeline that turns video into structured, citable, queryable JSON scene graphs, enabling AI assistants to analyze and search across video libraries without re-processing.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Your agent seeks what search can't find. A self-hosted perception MCP server that transcribes speech, reads behind logins, sees images and video frames, crosses languages, and remembers.

Read-only MCP access to the p-e relay store: an append-only corpus of provenance-bearing coordination records, with tools to fetch a record by id, list records and replies, and check existence. This image serves a snapshot frozen at build time; append_relay is listed but refused, and deposits to the live store require an HMAC-signed request.

Turn any YouTube video, article, PDF, or image into a reusable Claude Code skill — without leaving your editor.

Gives every AI agent working in a repository a shared, persistent knowledge graph stored in a plain JSONL file, with each entity, relation, and observation tagged with the date and agent that added it. Provides tools and prompts for searching, editing, renaming, merging, cleaning up, and exporting that memory, and keeps it locked to the repository that owns it.

Universal MCP knowledge server for LLM agents, powered by local RAG, providing domain-specific best practices and playbooks across software engineering, marketing, video editing, and other knowledge areas.

AI reads your codebase like a book - one page at a time. Pharaoh gives it the index and a map of how every chapter connects.

Connects to Obsidian vaults via the Local REST API plugin, enabling AI-assisted Zettelkasten workflows including creating atomic notes, searching content, managing links and tags, and performing precise content editing operations.

MCP server that lets agents create and update persistent concept maps via the NodeLand API, returning shareable URLs for humans to view, embed, and keep editing.

Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.

A standalone Node MCP server that provides semantic search, knowledge graph, and vault editing over an Obsidian vault. It runs locally as a single stdio process without requiring an Obsidian plugin for core functionality.

Self-hosted MCP server for Obsidian with semantic + full-text search over PostgreSQL/pgvector, wikilink graph traversal, atomic note CRUD, OAuth 2.0, and a self-describing vault guide.

Provides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.

Enables agents to check and retrieve concept-structured YouTube video summaries from the oratilo library via lookup and full-text search tools, avoiding redundant summarization work.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

Provides a hybrid memory architecture with a thin SQLite index and Markdown cold storage, enabling AI agents to write, query, link, and rebuild long-term memories via MCP tools, model-agnostic and zero third-party dependencies.

Enables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.

A persistent, project-scoped memory layer for AI agents, supporting hybrid retrieval (vector, keyword, and tag matching) and sharing across different MCP clients like Claude Code, Qoder, or Cursor.