"An article or written content" matching MCP servers:

Enables local Vietnamese ecommerce copy preparation, source-grounded RAG retrieval, offline voice previews, correction-memory feedback, hook review, and fine-tuning dataset preparation without publishing posts or approving audio.

Read-only MCP server for a content contract layer: protocol, modules, pipelines, assets, library. 一句话 / One-liner（ZH）：给任何 AI agent 一个可校验的内容规范与资产底座——先查契约，再落笔。 描述 / Description：只读 MCP 服务器：把长内容的验收标准（协议 / 模块 / 管线 / 资产 / 馆藏）变成 agent 可调用的检索与取件工具面。10 个只读工具 + 1 个 prompt（assemble_guide）；支持 modern 2026-07-28 与 legacy 2025-11-25 双协议；零第三方依赖（Python 标准库）；无写路径。 仓库 / Repo：https://github.com/Monyeah777/NinFenz 站点

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.

Bintu fetches a public webpage through MCP and returns cleaned text or chunks for AI-agent workflows. It is designed to reduce page clutter while preserving the source content needed for context.

Enables developers and AI agents to compress context, plan token budgets, rerank results, patch code, analyze ASTs and dependencies, isolate stack traces, compile polyglot types, solve deterministic math, schedule constraints, judge A/B tests, and diff agent memory checkpoints through 12 specialized tools.

Enables AI agents to capture clean web screenshots and extract main article content from any web page, with automatic removal of cookie banners, ads, and boilerplate.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

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.

Enables AI agents to perform keyword, semantic, hybrid, and SQL retrieval over data stored on object storage or local paths, using a local embedding model without requiring an API key.

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-based conversational HR agent that handles time tracking queries, policy lookups, adjustment approvals with human confirmation, and BigQuery analytics via natural language.

An MCP server that enables searching Merill's Weekly Microsoft AI Roundup archive with natural language queries, returning sourced excerpts, issue details, and tool mentions. It supports hybrid semantic and keyword search, issue retrieval, and archive browsing with no API keys required.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

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.

An MCP server that indexes a repository locally and provides keyword, semantic, hybrid, and SQL search tools, enabling coding agents to answer questions about the codebase efficiently without reading files one by one.

MCP server for Scrapiq, providing a tool to extract clean content from URLs. It returns title, content, links, and metadata in text, markdown, or JSON formats.

Enables AI agents to ingest documentation from websites or local files and perform semantic search over the indexed content using pgvector-backed embeddings.

An MCP server that enables web search and page content retrieval via the Keenable API, supporting search with filters and fetching clean markdown content from indexed URLs.

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.

An enterprise-grade Model Context Protocol server for high-performance web analysis that discovers subpages, provides AI-based page summaries, and extracts structured content for RAG using FastMCP and FastAPI.

An MCP server that allows AI assistants to search and retrieve human-curated content recommendations from Copus.

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.

An MCP server that enables saving, retrieving, and managing research content using ChromaDB vector storage and semantic search.

Provides content agents with structured search over editorial guidelines, visual templates, and past post outcomes, enabling auditable proposals that cite rule IDs.

An installable MCP server that reviews diffs/PRs against a target repository's own coding conventions, learned via RAG over its code, docs, and lint config, citing specific file:line sources.

Enables Codex, ChatGPT, and Aside to share project work memory by reading private GitHub-backed checkpoints and searching or re-reading allowed local/SSD documents through read-only MCP tools.

An MCP server that enables processing of massive datasets up to 10M+ tokens using a recursive language model pattern for strategic chunking and analysis. It automates sub-queries and result aggregation using free local inference via Ollama or the Claude API to handle context beyond standard prompt limits.

Provides access to Jina AI's suite of web tools including URL reading, web/image/academic search, content extraction, embeddings, and reranking capabilities. Enables AI assistants to search the web, extract content from URLs, and process information with semantic understanding.