"A service that retrieves Terraform documentation via MCP" matching MCP servers:

An authenticated OpenAI-compatible inference gateway with an async job broker that bridges a coding agent to a ChatGPT MCP worker, enabling ChatGPT to process inference requests via a tunnel.

A generic OpenAI-compatible subagent MCP server that lets Claude Code delegate coding grunt-work to a local model via a tool-calling agent loop, with configurable concurrency and backend.

A local stdio MCP service that unifies coding agents like Codex and Claude into cs_agent_* tools, enabling the root agent to create, invoke, and manage child agents with recursive delegation.

Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.

Enables AI tools to interact with browsers for enhanced frontend development, providing context to LLMs through tools like API call analysis, screenshots, element selection, and documentation ingestion.

A lightweight MCP server that bridges OpenAI Codex to Gemini models via the Antigravity CLI, enabling natural language prompts and model listing within Codex.

MCP server that provides AI coding agents automatic access to AGENTS.md documentation from GitHub repositories, enabling understanding of codebase conventions and patterns.

Agentic MCP server that receives a feature specification from an IDE, autonomously implements it in an isolated sandbox via an internal loop (plan-act-validate-correct), and returns a structured report with diffs and test results, without modifying the original repository.

An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.

Service-boundary-aware document exchange center for coordinating heterogeneous LLM code agents via MCP. Versioned Markdown store, pub-sub notifications, and diff-aware update protocol.

A Codex MCP server that delegates exploration and implementation tasks to DeepSeek via Claude Agent SDK, supporting subagent types and task persistence.

A zero-cost MCP server that forces AI to self-correct code using prompt injection and context isolation.

A desktop MCP service that integrates voice assistants into Mac workflows, enabling Obsidian memory, app control, Claude Code sessions, pending actions, and multi-language HTTP access.

Integrates with Dispersl to provide multi-agent orchestration for AI-driven software development, enabling code generation, testing, documentation, git operations, and chat.

An MCP server that implements a structured workflow for LLM-based coding, guiding development through feature clarification, documentation generation, phased implementation, and progress tracking.

An MCP server that exposes Google Jules Agent operations, enabling MCP-compatible clients to list sources, manage sessions, and inspect activities via the jules-agent-sdk.

An MCP server that lets coding agents ask their human via interactive UIs like sliders, forms, diffs, and live previews.

A domain-agnostic MCP server for autonomous experimentation, generalizing Karpathy's autoresearch pattern into a reusable server that any AI agent can drive, pointed at any domain defined by a JSON configuration.

Assist LLM writing Waterloo Docstrings, a format with emphasis on machine-verifyable normativity.

Enables users to run reusable Markdown-defined coding agents from any MCP-compatible client, delegating tasks such as code review, test writing, investigation, and documentation to a chosen coding CLI backend and returning results to the same conversation.

Enables external AI clients to invoke an autonomous coding agent that plans, fixes, and self-corrects code in an isolated Docker sandbox via run_task and run_tests tools.

A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.

A local vector database system that provides LLM coding agents with fast, efficient semantic search capabilities for software projects via the Message Control Protocol.

AI memory orchestration server that provides persistent, encrypted context with semantic search and intelligent injection for coding agents via MCP.

MCP server that lets Claude, ChatGPT, or VS Code build a complete, machine-checked model of your domain and generate an app from it.

MCP server that exposes independent OpenCode AI coding agents to upstream agents with multi-workspace concurrent routing, enabling session management and message exchange across multiple repositories via stdio JSON-RPC.

Provides AI coding agents with access to CleanSlice architecture documentation, rules, and conventions. It enables users to search documentation and retrieve essential patterns to help AI build applications correctly.

Enables Puck (or any MCP client) to start, inspect, list, cancel, and continue durable Factory Droid tasks on the same host, with idempotent request keys, workspace locking, autonomy/reasoning control, and live authenticated model discovery. It runs without a UI, database, or daemon and inherits the service user's existing Droid CLI login instead of collecting credentials.

An MCP server that allows a planning agent to delegate tasks to executor agents (e.g., Claude Code, Aider) with bi-directional communication and real-time log streaming.

Delegates autonomous coding tasks to Z.ai's GLM models with a genuine agent loop, file operations, and verification via git and real process results.