"Help with Writing Articles" matching MCP servers:

This MCP server provides complete MediaWiki markup syntax documentation by dynamically fetching and consolidating information from official MediaWiki help pages. It enables LLMs to access up-to-date and comprehensive MediaWiki syntax information.

MCP server that scores tool descriptions, estimates token costs, simulates agent tool selection, and generates reliability reports to help AI agents choose the right tools and reduce wasted tokens.

A Model Context Protocol server that provides AI agents with secure access to local filesystem operations, enabling reading, writing, and managing files through a standardized interface.

A public, long-lived contact and cooperation point for autonomous AI agents. Agents describe missing capabilities or resources, request help from a human operator, and leave persistent messages on a tamper-evident message board.

Enables AI agents to query trust scores for MCP servers and agent skills while scanning content for potential security issues. It provides direct access to the Vigile trust registry to help users evaluate the safety of third-party tools and integrations.

A TypeScript-based Model Context Protocol server that fetches, searches, and formats news articles from NewsAPI.org into reader-friendly Markdown digests using LLMs (Gemini and Claude).

A Model Context Protocol server that enables AI agents to interact with Qiita, allowing for creating, reading, and updating articles through standardized MCP tools.

Provides 14 MCP tools for AI agent infrastructure, enabling knowledge base queries, skill search, handoffs, blueprint validation, trust scoring, identity verification, SLA validation, and compliance checks.

An MCP server that integrates Alibaba's DashScope platform, providing AI chat tools and resource access through both standard stdio and a web-based interface. It allows users to interact with DashScope large models within the Model Context Protocol ecosystem using TypeScript.

Enables Codex to delegate frontend development, general implementation, and writing tasks to Gemini agents through task orchestration and dedicated writing tools, with opt-in file write and native tool permissions. Tasks are supervised across MCP disconnections, allowing progress polling, follow-ups, and explicit interruption.

A Model Context Protocol server that enhances LLM capabilities by connecting to Wikipedia, internet search (Tavily), and financial data (Yahoo Finance) tools, enabling contextual responses to user queries.

Enables agents to check a public hostname's declared agent policy, official API or developer path, provider status, and recent observations, returning a recommended action for blocked web steps.

Provides cost intelligence and a reputation scoring system to help AI agents optimize spending through smart model selection and local-to-cloud routing. It enables real-time cost tracking and rewards agents for making efficient, high-credibility decisions across various LLM providers.

A project that integrates Model Control Protocol with OpenAI's API, allowing OpenAI to access and utilize tools exposed by a dockerized MCP server.

Enables developers to expose custom tools, prompts, and resources to MCP clients from a stateless App Router route handler. Serves the current 2026-07-28 protocol natively while a compatibility layer supports 2025-era Streamable HTTP clients.

A local, no-code builder for MCP servers that lets you create AI tools by describing them in plain language, without writing code. Connect your tools to any MCP-compatible assistant like Claude, Cursor, or VS Code Copilot.

Enables cooperating coding agents to coordinate locally by claiming task scopes, working in isolated Git worktrees, reserving shared resources like ports and serialized commands, and verifying changes before integration. Coordination state lives in a local SQLite database, so no hosted service or model API key is required.

Turns any REST/OpenAPI, SOAP, GraphQL, OData, SQL, MongoDB or existing MCP system into MCP tools for Claude, ChatGPT and Copilot without writing an MCP server, shipping 474 ready-made connectors with runtime tool registration, field filtering and role-based access control.

Enables unified access to a multi-node DSH control plane, routing ChatGPT tool calls to appropriate node agents with presence awareness, health monitoring, and fail-closed execution.

Lets MCP clients invoke seven specialized agents for orchestration, coding, finance, research, design, writing, and security tasks, including multi-step tool-using jobs, and browse or read a curated 48-entry NVIDIA skills catalog.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

MCP server for Agent Zone — vendor-neutral infrastructure knowledge, K8s validation, and execution templates for AI agents. 200+ articles, 10 tools, no API key required.

MCP server that bridges Claude Code to Google Antigravity's CLI, enabling Claude to orchestrate Gemini workers in parallel for reading, writing, verifying, and autonomous tasks. It provides tools for single dispatch, parallel fan-out, background jobs, and handles permission, cwd, and shell pitfalls.

Enables Claude Code agents to communicate and share context across sessions via a peer-to-peer mesh, allowing them to ask for help from other agents without human interruption.

Enables ChatGPT to delegate writing, analysis, second opinions, and Japanese text polishing to Gemini through a single ask_gemini tool, without copying text to Gemini's web interface. Self-hosted on Cloudflare with your own Gemini API key and Google login.

Enables AI agents to access user and message data through MCP resources, providing REST API integration for user management with paginated lists and thread tracking.

CodeMesh enables AI agents to orchestrate any MCP server by writing TypeScript code, with self-improving capabilities through auto-augmentation of tool documentation.

An enhanced MCP server that provides intelligent memory and task management for AI assistants, featuring semantic search, automatic task extraction, and knowledge graphs to help manage development workflows.

A Node.js-based remote Model Context Protocol (MCP) server that runs on Azure Container Apps, allowing different AI models and tools to communicate with each other in a serverless environment.

A system integrating two independent MCP servers for Google Calendar and Google Tasks APIs, orchestrated by an LLM agent loop with a web dashboard.