"MCP server for finding research data and models for AI/ML training" matching MCP servers:

Lets a coding agent hand a plain-language app idea to a hosted AI software team that shapes, designs, builds, tests and deploys it, returning a one-time link into the full build workspace. Also lists your apps with their stage, pending approvals and live addresses after a standard OAuth sign-in.

A local MCP server that lets Hermes supervise Claude Code, delegating focused coding, research, or review tasks to the Claude Code CLI and managing worker sessions, background jobs, cancellations, and read-only reviews.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

Bridges Claude Code CLI with Cursor IDE to use your existing Claude subscription without separate API costs.

Enables MCP clients to drive local Codex on a target Git repository: inspect repo state, start and follow up on tasks, review events and diffs, and record audit evidence for research governance.

Enables Windows users to connect Antigravity CLI as an MCP subagent for coding tasks such as file reading, code execution, edits, and terminal commands, with model selection, conversation continuity, and streaming progress.

An MCP server that enhances Claude Code with evidence-first engineering, protocol gates, project-aware verification, auditable traces, and durable autonomous execution.

Enables AI coding agents to read and write a user's Figma file through the Figma Plugin API, offline and privately, without API tokens or rate limits.

The most advanced MCP server for Godot Editor that lets AI assistants operate directly inside your running Godot project for scene creation, script generation, UI authoring, and more.

Enables primary AI orchestrators to delegate token-heavy coding tasks to economical models via OpenRouter, running sandboxed autonomous ReAct loops with filesystem operations and git audit tools while reducing token costs.

Enables running multiple AI CLI tools (Claude, Codex, Gemini, Forge, OpenCode) as background processes with automatic permission handling, allowing LLMs to execute async multitasking and combine different AI models.

Forecast time series in CSV files: deterministic skforecast workflows and the script that ran.

Enables MCP clients to run Cline CLI prompts and isolated repository-wide analyses, returning terminal text responses with model, duration, and usage/cost.

Lets AI coding agents ask a Rails app about itself: 35 read-only tools answer from the schema, models, routes, controllers, views, jobs and conventions, over MCP or the command line, even when the app cannot boot.

Enables acceptance gates for AI coding-agent runs by recording evidence, running deterministic validation, applying a quality gate, and rendering auditable outcomes.

Enables Claude to hand scoped, implementation-only coding tasks to any model available in a local opencode install — including Kimi, GPT, Gemini and local models — and to run many of them in parallel. Claude stays the orchestrator: it briefs each worker, collects results and needs-flags, then reviews diffs and runs tests, lint and builds itself.

Enables Codex to start the local DeepSeek Harness Web UI, delegate coding tasks into visible sessions, and review workspace changes.

Provides token-efficient code retrieval for coding agents by indexing repositories and enabling ranked snippet search, symbol outlines, and surgical line reads.

Turns product ideas into implementation-ready planning packages including PRD, requirements, user flow, wireframes, data schema, API contracts, and SDK boundaries, with an MCP handoff for coding agents.

Provides AI-powered development tools including code generation, refactoring, debugging, performance optimization, and test generation, along with smart prompts for code analysis and documentation, and a built-in knowledge base of coding best practices.

Integrates AI Consensus into coding agents, routing decisions through three frontier AI models for independent analysis and cross-examination, returning a recommendation and strongest dissent.

Enables Sublime Text to integrate with Claude Code via the IDE protocol, providing in-editor diff review, selection context sharing, and @-mentions through a local WebSocket/MCP server.

Enables managing Linux hosts and local coding agents from an MCP client through shell commands, files, background jobs, system information, instruction and skill discovery, and optional Claude Code, Codex, or Cursor CLI conversations. It provides privileged remote access with token authentication and can run longer work in the background.

Enables IDE integration with a multi-agent AI pipeline for solving, reviewing, and optimizing code through adversarial peer review and security filtering.

Enables AI-powered coding assistance including file editing, code generation, explanation, review, and shell command execution, using multiple free AI providers with automatic fallback.

Enables AI agents to delegate complex coding tasks, refactorings, and automated code reviews to OpenAI Codex and Google Antigravity CLIs, running them autonomously in YOLO mode with process supervision.

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.

Provides 23 modular tools for competitive programming, including problem analysis, algorithm planning, code generation, verification, testing, code review, and learning assistance.

A policy layer between ChatGPT and the official Codex MCP server, adding safety controls like read-only sessions, approval policies, and secret scanning for secure daily use.