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    A generic local MCP plugin base for ChatGPT that ships example status and echo tools, a guided setup wizard for tunnel configuration with DPAPI-protected API keys, and separated persistent versus generated runtime storage. It also provides a bounded metadata-only conditional-read cache that suppresses unchanged read-only responses to save context.
    2
    MIT
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    B
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    Enables ZCode to control a real Chrome browser, including tabs, navigation, page content, clicks, form filling, keyboard input, scrolling, screenshots, and JavaScript evaluation through a local MCP bridge.
    MIT
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    Enables cluster-aware command execution and automatic task routing across distributed nodes based on system load, architecture, and OS requirements. It supports parallel execution, remote node management via SSH, and dynamic load balancing for agentic workflows.
    4
    MIT
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    An MCP server that helps AI coordinate sequential tool calls and maintain a comprehensive journal of execution workflows, decisions, and actions.
    MIT
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    B
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    Enables ChatGPT to delegate writing, analysis, second opinions, and Japanese text polishing to Gemini through a single ask_gemini tool, without copying text to Gemini's web interface. Self-hosted on Cloudflare with your own Gemini API key and Google login.
    180 npm
    MIT
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    Enables a single Antigravity IDE to explicitly drive multiple isolated Antigravity CLI workers, choosing each worker's account, model, skills, task, and expected outputs while the bridge executes those decisions over STDIO with SQLite-backed task state. It returns bounded logs, cancellable task control, and immutable artifact exports whose chunks and whole files can be verified by SHA-256.
    1
    MIT
  • F
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    A
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    Enables Codex to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited, idempotent progress events backed by a matching project-record Git commit. Access is scoped to one workspace and project via short-lived, revocable, hash-stored credentials that cannot reach members, keys, deletion, publication, or deployment.
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    Exposes Coze workflows as MCP tools, allowing AI clients to discover and execute workflows from a specified Coze workspace. It provides a simple way to integrate external skills into platforms like OpenClaw without needing local environment configurations.
    96
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  • F
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    Enables MCP clients to read a project's Git-backed kickoff, acceptance criteria, handoff package, progress, and next step, and to append validated, audited progress events as project records. It provides short-lived scoped credentials and fail-closed tool allowlisting for safe, resumable AI-assisted development.
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    A template for deploying remote Model Context Protocol servers to Cloudflare Workers using Server-Sent Events (SSE) without authentication. It enables developers to build and host custom tools that can be accessed by local clients like Claude Desktop or the Cloudflare AI Playground.
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    Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.
    1
    7
    MIT
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    license
    A
    quality
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    maintenance
    An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.
    1
    1
    MIT
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    maintenance
    A tool that allows deployment of a Model Context Protocol server on Cloudflare Workers without authentication requirements, enabling users to create and use custom AI tools via the Cloudflare AI Playground or Claude Desktop.
    3 npm
    ISC
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    A type-safe solution that enables remote access to Model Context Protocol (MCP) services, allowing clients to connect to centralized MCP implementations without waiting for official remote support.
    3
    MIT
  • F
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    Enables users to describe an LLM fine-tuning workload once and receive ranked, task-aware GPU recommendations across a dozen cloud providers based on required VRAM/FLOPs, cost, and runtime. It surfaces the cheapest, fastest, and balanced options through MCP so coding assistants can plan training hardware without manual price comparison.
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