"Simple HTTP server or client implementation" matching MCP servers:

MCP server for DeepSeek AI models (Chat + Reasoner). Supports multi-turn sessions, model fallback with circuit breaker, function calling, thinking mode, JSON output, multimodal input, and cost tracking.

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.

This MCP server enables remote control and management of Claude Code agents, allowing you to execute missions, configure agent personalities, and integrate with other MCP tools.

Bridges MCP clients such as Claude Code and Cursor to independent Codex app-server sessions, letting them start, poll, steer, review, compact, cancel, and answer prompts for asynchronous Codex tasks over local stdio or a remote authenticated WebSocket. Runs read-only by default, with workspace-write sandboxing only when a user explicitly enables it, and reports job status, model listing, and progress back to the client.

Connects AI coding agents to Autodesk Fusion 360 for CAD automation, enabling natural language control over sketching, 3D modeling, and CAM operations. It uses a Python-based bridge and a custom add-in to execute over 80 tools ranging from simple geometry creation to complex assembly and parameter management.

An open-source MCP server that connects your IDE or AI assistant to the Codex CLI, enabling non-interactive automation with codex exec, safe sandboxed edits with approvals, and large-scale code analysis via @ file references.

An MCP server that exposes Fabric patterns as tools for Cline, enabling AI-driven pattern execution directly within Cline tasks.

Send requests to OpenAI, MistralAI, Anthropic, xAI, or Google AI using MCP protocol via tool or predefined prompts. Vendor API key required

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Enables agents to generate typed client code from OpenAPI, GraphQL, Protobuf, and SQL specs using MetaEngine's code-generation platform.

Enables a chat or voice assistant to drive coding agents running in herdr: it can start an agent on a task, list and watch sessions started anywhere, send follow-ups, answer an agent's questions and approve or refuse its permission prompts. Long-running work is reported back through webhook callbacks so the conversation can continue without blocking.

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.

Send requests to OpenAI, MistralAI, Anthropic, xAI, or Google AI using MCP protocol via tool or predefined prompts. Vendor API key required. Both STDIO and SSE transport mechanisms are supported via arguments.

Wraps OpenAI Codex CLI as an MCP server, exposing 8 Codex tools (exec, review, skill list, skill run, status, poll, list jobs, kill) as named tools for use with pi or codex.

Exposes DeepSeek Harness agent capabilities over MCP so any MCP client can delegate real coding work to a running agent with its full toolset (bash, filesystem, todo, web). Turns are dispatched asynchronously into sessions and then tracked through status, tail, wait, cancel, compact, and rename tools, with the session log as the source of truth so results survive restarts.

Enables orchestrator models to delegate code creation and editing to Cursor's Composer 2 or Grok 4.5 agents, keeping the orchestrator's context free and shifting bulk code generation to cheaper agents.

Exposes DeepSeek Harness agent capabilities as an MCP server, letting any MCP client drive Harness to execute real coding tasks with structured results, context isolation, and parallel execution.

An MCP server that exposes the Symbols/DOMQL v3 AI assistant capabilities to any MCP-compatible platform. Enables generating components, pages, projects, and more from natural language, as well as searching documentation and reviewing code.

An MCP server wrapping the Cursor CLI agent, enabling Claude Code and other MCP clients to delegate tasks to Cursor's AI agent for file writing, bash commands, and codebase queries.

Enables structured, step-by-step problem-solving through dynamic thinking processes that can be revised, branched, and adjusted as understanding deepens. Supports breaking down complex problems into manageable steps with the ability to revise previous thoughts and explore alternative reasoning paths.