"Information about dbt (Data Build Tool or other meanings)" matching MCP servers:

A Model Context Protocol (MCP) server that wraps the dbt CLI tool, enabling AI coding agents to interact with dbt projects through standardized MCP tools. Developed by Mammoth Growth.

MCP server that provides a single run_grok tool to execute Grok build agent tasks in a specified working directory, automatically reusing sessions and returning results with logs.

MCP server connecting Claude/Cursor to Codex CLI, enabling code analysis via @ file references, multi-turn conversations, sandboxed edits, and structured change mode.

Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.

This is a powerful Model Context Protocol (MCP) server that integrates multiple AI coding agents—Anthropic Claude Code, OpenAI Codex, and Google Gemini—directly into your workflow. It enables seamless cross-provider analysis, leveraging Gemini's massive token window, Codex's specialized coding capabilities, and Claude's advanced reasoning.

An MCP server that allows Claude Code to interact with the OpenAI Codex CLI.

Enables Claude Code to dispatch opencode CLI tasks as background processes with immediate task handle return, status polling, and result retrieval, avoiding tmux and log parsing issues.

Official implementation of Anthropic's 'think' tool that provides Claude with a dedicated space for structured reasoning, improving performance by up to 54% on complex tasks requiring multi-step problem solving.

Local stdio MCP bridge that delegates coding work to the Grok CLI agent via isolated git worktrees and typed receipts. Provides MCP tools for interacting with the Grok CLI across stdio, WebSocket, and legacy transports.

a claude code harness engineering tool

An autonomous, extensible LLM build orchestrator. Give it a repo and a goal; it decomposes the goal into tasks, edits code, and gates every change on build/tests/lint, reverting regressions. Polygot, cost-aware model selection, pluggable via entry points. Ships as an MCP server so any client can drive it in plain English.

Enables ChatGPT or other MCP clients to control native Codex sessions on Windows, providing tools for thread management, turns, observation, steering, and responding to approvals.

Production-ready MCP server starter templates in TypeScript and Python. Includes tool, resource, and prompt patterns with Claude Desktop integration configs.

A minimal local MCP server that lets Claude Desktop or Claude Code delegate coding tasks to Grok Build running headless as a subagent.

Delegate tasks from Claude Code to other models (Codex CLI, DeepSeek, OpenRouter, etc.) without leaving the app.

The IDE for agents — read by symbol, edit against a revision, validate with your own build, revert. It is a local stdio MCP server for coding agents. It reads code by symbol with tree-sitter and real language servers (Go, Java, Scala, TypeScript, Python, Rust, Ruby), edits against a known revision and returns compiler diagnostics with each edit, runs the repository's own build, test etc.

Provides per-Subagent MCP controls to any coding agent or client across all your MCPs and prevents context window waste. Loads only 3 tools instead of all your MCP Server's tool definitions. Agents discover tools on-demand, only when needed and only the servers and tools they are allowed.

Enables AI assistants and other MCP clients to launch and steer Cursor Cloud Agents on repositories or as repo-less research tasks, including model selection, mid-run follow-ups, cancellation, result retrieval, and run listing. Also exposes authentication checks and per-agent or per-run token usage and cost reporting.

Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.

MCP server that analyzes videos locally with frame-by-frame understanding and optional browser sidecars, producing structured context bundles for coding agents to fix bugs, add features, or build new functionality.