"Researching an author based on their books" matching MCP servers:

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

Enables ChatGPT to work on a local project by reading and editing files, running shell commands, keeping terminals and desktop sessions open, and splitting work across durable workers whose context persists between tasks. Long-running work can be steered mid-flight, tracked with Goal, and carried into fresh chats via Compact & Resume.

Lets ChatGPT work directly on a local project by reading and editing files, running shell commands and tests, keeping terminals open, and using the user's desktop, all paired with an approved workspace folder. It also splits independent jobs across persistent workers that retain context, while riding the user's existing ChatGPT plan rather than Codex quota.

Plori runs AI agents in Workspaces. A Workspace is a project folder in the cloud. Several agents can work in it at the same time, each on its own copy of the files, and Plori merges their work back into the folder. Every version of the files is kept.

An MCP server giving coding agents context-window-aware code search and safe, atomic multi-file edits — built to cut token usage on large codebases without sacrificing correctness.

Enables Claude Code to use GLM (Zhipu) as a cheap, full-capability subagent for file editing, code generation, and bash commands, with automatic routing between Opus and GLM based on task complexity.

Shared, code-grounded memory for developers and their coding agents. Capture a learning once and the whole team plus every agent recalls it; memory is grounded in your code and stored as git-tracked JSON reviewed in PRs, with citations validated on write and stale memory withheld from recall. Works with any MCP client.

Allows two AI coding agents on different machines to securely pair and share files, context, and conventions through an end-to-end encrypted peer-to-peer channel with human-in-the-loop consent.

An MCP server that lets coding agents scaffold, run, and iterate on Maltego transforms against a live local server, reading back entity results to validate and improve mappings.

An MCP server that enables Claude to orchestrate multiple autonomous Claude Code agents working in parallel across different projects, with tools to dispatch, monitor, and manage their progress.

Enables delegating local background tasks through an existing Codex or Claude Code subscription login and retrieving their status, answers, and usage.

Enables multiple AI agents to coordinate work on the same codebase by providing real-time file locking, commit approval, and agent awareness through a lightweight WebSocket-based MCP server.

Connects AI coding agents to the SkillsMP marketplace, allowing users to search, read, and install over 8,000 community-made skills. It enables agents to gain new capabilities either through on-the-spot instruction or permanent installation without requiring an API key.

Turns a Claude Desktop or Claude Code conversation into an orchestrator for parallel AI coding agents, each running in its own Tern terminal tab and git worktree on its own branch, with any model available on the machine. It enables starting, monitoring, correcting, and merging agents—reading their reports and diffs, switching models or thinking levels mid-task, and enforcing model policies.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

An MCP server that allows coding agents to look up contextual rules and patterns on demand, providing just-in-time guidance for specific tasks like writing tests or authoring UI.

ast-mcp-server gives coding agents compact, type-aware access to TypeScript and JavaScript projects, providing structural code tools based on the real compiler project model through ts-morph for declarations, references, renames, and diagnostics, with safe prepare → review → apply mutation semantics and immutable hash-bound plans.

An MCP server that lets AI coding agents work on Godot 4 projects, including reading and editing scenes, writing and validating GDScript, running the game, and capturing screenshots.

Connects AI assistants to the Repovive competitive-programming platform, enabling them to browse problems and contests, judge and submit code for real verdicts, track ratings, communicate with users, and author verified problems and rounds.

An MCP server that enables AI clients to autonomously discover, analyze, fix, test, submit, and track open-source contributions on GitHub through specialized tools.

Enables Codex CLI to delegate tasks to file-based specialized agents with isolated execution, auditability, and CI-friendly validation.

Enables developers to delegate asynchronous coding tasks to a cloud-based autonomous agent, creating tasks, reviewing and approving execution plans, sending feedback, monitoring sessions, and retrieving diffs and Pull Requests directly from an MCP-compatible IDE. It also supports configurable mock mode for local testing without consuming API credits.

Delegates heavy development tasks from a supervisor to an autonomous worker on a cheaper model via MCP, with isolated git worktrees and provider-agnostic support.

Orchestrates multiple Claude Code agents across iTerm2 sessions with process-level isolation, enabling collaborative AI development workflows on multiple codebases with task-based inter-agent communication and persistent state management.

MCP server that turns ChatGPT Web or any MCP client into a coding agent on your own repositories, enabling file editing, command execution, testing, and git workflow without an OpenAI API key.

Automatically generates compelling application specifications and code based on the four dimensions (existence, historicity, relationality, irrationality), simplicity, and Figma-like UI, enabling users to create great apps without detailed instructions.

An MCP server that enforces hard quality gates on AI coding agents, including forced web search, planning, and empirical test execution, to prevent common failure modes and ensure production-grade code.

One shared project for your team's Claude Code, Codex, Cursor and OpenCode agents: a task board, decisions and handoffs. Everyone keeps their own plan.

An MCP server for managing, editing, and running Stata .do files, integrating with Claude Desktop to enable natural language control of Stata analysis on macOS.

An MCP server for Trae AI that enables automated creation and management of OpenSpec-compliant projects through natural language descriptions. It features tools for generating specification files, optimizing existing code based on specs, and deploying project templates without command-line intervention.

An MCP server for local Cocos Creator 3.8 automation, enabling coding agents to create projects, edit scenes, and build WeChat Mini Games directly on a developer machine.

Enables AI coding agents on different machines and accounts to work one repository as a team by declaring file and symbol claims before editing, so collisions are refused up front rather than discovered at merge. It also supports delegating tasks between teammates' agents, which do the work with their own tokens and commit, with replies, commit shas, claims and messages landing on one shared board.

Enables ChatGPT to delegate coding tasks to Codex running locally on the user's machine, using their ChatGPT sign-in and Codex plan limits without separate API billing. It checks quota limits and returns changed files and command output for review.

Outcome-based persistent memory for AI coding tools.

An MCP server leveraging the Rust-based ty type checker to provide AI models with high-performance, semantic Python code analysis and structural navigation. It enables precise symbol searching, cross-file renaming, and diagnostic reporting to improve code understanding and editing accuracy.

An MCP server for automating Google Jules that enables seamless integration for task creation, code analysis, and AI-powered development workflows. It supports multiple session modes including Browserbase and cookie-based authentication for both local and cloud environments.

A Model Context Protocol server that provides powerful regex-based code refactoring and search tools for Coding Agents.

Enables collaboration between multiple AI models (GPT, Claude, Gemini) to work together on complex tasks, with intelligent task distribution and role-based expert assignment for code development, review, and optimization.

Always-on AI agents: a software factory for Claude Code, or an AI SRE that watches your systems.