"An article or written content" matching MCP servers:

Provides redacted access to a private local knowledgebase for coding agents, allowing them to inspect files while hiding sensitive names and identifiers.

Lossless archive and search for AI agent sessions (Claude Code, Codex, opencode, pi and others), exposed to agents over MCP. Local-first, written in Rust.

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.

An MCP server for managing contextual data as markdown files with metadata, enabling agents to save, retrieve, search, and delete contexts using simple CRUD operations.

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

Exposes AgentHive's member-level calls—including retrieve_context, log_session, create_agent, list_agents, create_task, and list_tasks—as native tools for Cursor and Claude Code. It lets IDEs spawn a stateless local subprocess that makes plain HTTP calls to an existing AgentHive instance, so agents can retrieve reviewed team memory and log sessions without hand-written HTTP instruction blocks.

Provides AI coding tools with one local SQLite memory and rules store they can read over MCP, REST or the CLI, so facts, sessions and goals persist across sessions and shared rules are written into each tool's own instruction file. Runs entirely on your machine with no account, telemetry or network calls by default.

Free Industry 4.0 / IIoT tools, no API key or account: lint MQTT Sparkplug B topics, check a Unified Namespace (UNS) for naming and hierarchy problems, and run an industrial AI-readiness diagnostic for manufacturing digital transformation and smart-factory projects. Works in Claude Code, Codex and any MCP client.

An MCP server that provides on-demand skill discovery for AI coding agents by querying GitHub repositories, using BM25 search to return relevant SKILL.md content.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

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.

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

Provides an external context buffer so a local model can maintain session memory across long tasks and search and page through large documents without loading them whole into its limited context window.

A self-contained, in-memory graph database for AI Agents. Provides semantic code understanding through the Model Context Protocol (MCP).

Provides MCP tools to read, write, append, and edit prose sections of nodes, backed by an in-memory or substrate-direct (Urania) backend.

Enables querying Tom Osborne's voice-cloned AI agent with a 21,000-article marketing knowledge base and his interview corpus to get answers in his voice.

Exposes tools to ingest FigJam boards, retrieve context summaries, and answer free-form questions about the board content.

Enables MCP clients to search, organize, and read preserved article text from a Linkwarden bookmark manager, supporting both read and write operations with safety confirmations.

An MCP server that reads all your Claude Code project memory files and exposes them as tools. Lets any Claude instance — in any project, or via Claude.ai — query your full project history and preferences.

Search and read AiWiki — an encyclopedia of AI-coding pitfalls and LLM privacy protection written from the AI's first-person perspective. 120+ bilingual (EN/中文) entries with mechanism analysis and cited evidence, fetched live from the site index.

MCP server for World Anvil that enables browsing, searching, and managing world content, plus exporting complete copies for migrations or backups.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

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.

Give your AI persistent, structured memory and let humans see it too. It stores project knowledge as Markdown files in a hierarchical tree, accessible via MCP tools and a built-in Web UI.

Enables Claude Desktop and Claude Code to build, update, inspect, validate and compile workflows for the SOLVE-IT Workflow Builder from natural language, automatically laying out nodes and connections and checking them against the SOLVE-IT knowledge base. Each result is written as a JSON file for import into the builder, or returned as a share link when small enough.

An MCP server for the un.manned wiki that lets AI agents read and write wiki content securely without exposing API keys, with built-in guardrails for quotas, duplicates, and untrusted content.

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.