"AI Model CLI Tools and Orchestration Configuration" matching MCP servers:

MCP server that gives AI coding agents (Claude Code, Cursor, Cline, etc.) access to multiple AI models through Antigravity CLI and OpenAI Codex CLI, enabling mid-conversation model consultation and code review.

A Model Context Protocol (MCP) server that enables multiple AI agents to share memory, coordinate tasks, and collaborate effectively across IDEs and CLI tools.

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.

A TypeScript MCP server for launching, tracking, and managing external coding-agent runs across local and remote backends like Codex and Claude Code. It allows top-level agents to orchestrate subagents through tools for spawning tasks, polling events, and handling interactive sessions.

Enables running the same prompt(s) across roughly 300 models from Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, Qwen and others, then comparing per-model outputs, latency, token usage, error rates and billed cost side by side. Supports free cost estimates before launching, asynchronous run creation with status polling and cancellation, prepaid x402 credit top-ups, and an optional AI-written comparison summary of the results.

A multi-agent runtime that coordinates six specialized agents through a typed artifact pipeline with 41 RPC methods. It features dynamic autonomy levels and context sufficiency scoring that adjust agent behavior based on the operator's state and task requirements.

Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.

Enables AI agents to discover, compare, and select the best AI models across multiple providers based on pricing, performance, and capabilities, with real-time cost estimation and benchmarking.

Provides AI assistants with structured access to metadata for 76+ AI models across Ollama, Claude, and OpenRouter, enabling capability queries, compatibility checks, model comparisons, and task-based recommendations.

Automates enterprise Power Platform project setup and management via MCP, reducing setup time from weeks to hours through template-based provisioning, Azure DevOps orchestration, and direct API integration.

Enables querying AI model lifecycle and deprecation data across OpenAI, Anthropic, Google Gemini, and Amazon Bedrock, including model status, sunset dates, and recommended replacements via MCP tools.

Complete Vinted MCP and CLI Server

Discovers local model runtimes such as Ollama, LM Studio, and LocalAI, and exposes their endpoint metadata to MCP clients like Copilot.

CLI and stdio MCP server for noticed. Exposes ~50 noticed agent capabilities (network search across GitHub + LinkedIn, missions, PRM, memory, workspace, web search, cron, ...) via two meta-tools — search + execute — to any MCP-aware client (Claude Code, Claude Desktop, Cursor, ChatGPT).

Enables MCP clients to discover, inspect, and run 2,000+ AI models and data APIs, including search, social, scraping, image, video, and audio tools, through one browser-authorized local bridge. It also surfaces run status, recorded cost, and account balance, and supports rolling back client configuration changes.

Routes subagent tasks across Claude and OpenAI lanes by task kind and quota state, deciding whether to spawn a single model, run a duel of both vendors, or run both and ship the merge. It records duels with attested proof-of-run session ids, grades sides blind with one judge per vendor, and tracks per-kind standings and lane pacing.

Enables deterministic calculations for AI API and subscription costs, meeting time zones, recurring schedules, and cron next-run previews, returning normalized inputs, units, assumptions, dated sources, and links to results.

Delegates coding tasks to the locally installed Kimi Code CLI, reusing its auth, models, and configuration while adding tools for sessions, replies, model discovery, live turn steering, and history access.

Exposes the official lark-cli as an MCP server, enabling agents to execute arbitrary CLI commands, query API schemas, and manage authentication.

Persistent 3D/2D spatial world model MCP server for AI agents. Entity tracking, object permanence, AABB collision simulation & view frustum projection via local SQLite.