"How to connect with a Confluence page and retrieve its context" matching MCP servers:

Enables ChatGPT users to retrieve exact programming problems, submit C/C++ solutions only when explicitly requested, and track real judging verdicts through authenticated account linking.

Enables an agent to open a tldraw.com board in a controlled Chrome tab and draw on it by executing JavaScript against the page's own editor, so edits sync to the shared board. It also captures PNG exports of the view, page, selection, or specific shapes.

A Model Context Protocol server that enables natural language interaction with the Coverity Connect static analysis platform, allowing users to manage projects, analyze snapshots, and generate security reports through AI-powered interfaces.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

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.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

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.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.

MCP server to provide Sketch layout information to AI coding agents like Cursor

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Provides AI coding assistants with context optimization tools including targeted file analysis, intelligent terminal command execution with LLM-powered output extraction, and web research capabilities. Helps reduce token usage by extracting only relevant information instead of processing entire files and command outputs.

A Model Context Protocol server that enables LLMs to read, search, and analyze code files with advanced caching and real-time file watching capabilities.

Share code context with LLMs via MCP or clipboard

Connects ChatGPT to Roblox Studio's built-in MCP, enabling natural-language reading and writing of game data, including executing Luau code and modifying scripts and instances.

Context-Pods is a comprehensive development framework for creating, testing, and managing Model Context Protocol (MCP) servers. It provides a Meta-MCP Server that can generate other MCP servers through natural language descriptions or by wrapping existing scripts.

MCP server bridging ChatGPT to local OpenHarness tools, enabling file reads/writes, grep, LSP, and shell execution on a workspace.

Gives AI coding agents typed, mode-gated access to a real WordPress site — content, media, users and settings via core REST, plus PHP execution, SQL queries, filesystem operations and Elementor page read/build/patch/snapshot via a companion bridge plugin. Destructive actions and code execution are guarded by feature flags, explicit confirm literals, dry runs, redaction and audit logging.

Enables automatic weather information retrieval through a custom MCP server integrated with OpenAI using Cloudflare tunnels. Demonstrates seamless function calling between OpenAI and custom MCP tools without manual intervention.