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Alternatives

Products that do what MCPShark now supports Codex's config.toml does

  1. 1MA

    Quick update: MCPShark now supports Codex’s config.toml. If you use Codex CLI / the Codex VS Code extension, MCPShark will auto-detect ~/.codex/config.toml (or $CODEX_HOME/config.toml), parse the [mcp_servers] entries, and convert them into MCPShark’s internal config automatically (stdio + HTTP supported). Repo: https://github.com/mcp-shark/mcp-shark VS Code extension: https://marketplace.visualstudio.com/items?itemName=MCPShark...

    Dec 2025

  2. 2MT

    https://github.com/mcp-shark/mcp-shark Site: https://mcpshark.sh/ I built MCPShark, a traffic inspector for the Model Context Protocol (MCP). It sits between your editor/LLM client and MCP servers so you can: • See all MCP traffic (requests, responses, tools, resources) in one place • Debug sessions when tools don’t behave as expected • Optionally run “Smart Scan” checks to flag risky tools / configs

    Dec 2025

  3. 3

    A command center for working with agents

    Feb 2026

  4. 4

    Cloud agent for parallel dev tasks, powered by Codex-1

    2025

  5. 5

    Parallel custom agents for complex tasks

    Mar 2026

  6. 6

    Package Codex skills and app integrations as plugins

    Mar 2026

  7. 7

    A web code editor with AI & multi-language support

    2025

  8. 8

    An ultra-fast, single-binary MCP server written in Rust as a lightweight alternative to Node.js/Python. - StamManif/mcp-stama

    24d ago · github.com

  9. 9MW
  10. 10

    An open-source macOS client for Codex

    Mar 2026

  11. 11MS

    2025 · github.com

  12. 12CR

    Hey HN, I built pg-mcp, a Model Context Protocol (MCP) server for PostgreSQL that provides structured schema inspection and query execution for LLMs and agents. It's multi-tenant and runs over HTTP/SSE (not stdio) Features - Supports multiple database connections from multiple agents - Schema Introspection: Returns table structures, types, indexes and constraints; enriched with descriptions from pg_catalog. (for well documented databases) - Read-Only Queries: Controlled execution of queries via MCP. - EXPLAIN Tool: Helps smart agents optimize queries before execution. - Extension…

    2025 · github.com

  13. 13

    Live Codex task status in your macOS menu bar

    Aug 2026 · agentmicro.cc

  14. 14
    CodeX124

    Build webapps in minutes for completely free

    2025

  15. 15

    Agent-ready web context for any MCP client.

    Aug 2026 · docs.firecrawl.dev

  16. 16MV

    A few days ago I posted MCPShark (a traffic inspector for the Model Context Protocol). I just shipped a VS Code / Cursor extension that lets you view MCP traffic directly in the editor, so you’re not jumping between terminals, logs, and "I think this is what got sent". VS Code Marketplace: https://marketplace.visualstudio.com/items?itemName=MCPShark... Main repo: https://github.com/mcp-shark/mcp-shark Feature requests / issues: https://github.com/mcp-shark/mcp-shark/issues Site: https://mcpshark.sh/ If…

    Dec 2025

  17. 17MS

    Hey HN! I made this because Zig's stdlib changes so much and outdated docs are a problem. Server fetches the latest documentation directly from the ziglang.org and makes it available through the MCP, so LLM can query stdlib functions and builtins. Link: https://github.com/zig-wasm/zig-mcp

    2025 · github.com

  18. 18TO

    Prepend tomcp.org/ to any URL to instantly turn it into an MCP server. You can either chat directly with the page or add the config to Cursor/Claude to pipe the website/docs straight into your context. Why MCP? Using MCP is better than raw scraping or copy-pasting because it converts the page into clean Markdown. This helps the AI understand the structure better and uses significantly fewer tokens. How it works: It is a proxy that fetches the URL, removes ads and navigation, and exposes the clean content as a standard MCP Resource. Repo:…

    Dec 2025 · github.com

  19. 19

    Manage your CMS content from Claude, Cursor, and Codex

    12d ago · marblecms.com

  20. 20OS

    Large Language Models (LLMs) are powerful, but they’re limited by fixed context windows and outdated knowledge. What if your AI could access live search, structured data extraction, OCR, and more—all through a standardized interface? We built the JigsawStack MCP Server, an open-source implementation of the Model Context Protocol (MCP) that lets any AI model call external tools effortlessly. Here’s what it unlocks: - Web Search & Scraping: Fetch live information and extract structured data from web pages. - OCR & Structured Data Extraction: Process images, receipts, invoices, and handwritten…

    2025

  21. 21MO

    Hey HN - we built Morphik MCP to solve a common problem: finding specific information across scattered technical docs. We've experimented with GraphRAG, ColPali, contextual embeddings, and more. MCP emerged as the solution that unifies these approaches. Features: - Multimodal search across text, diagrams, and videos - Natural language knowledge base management - Fully open-source with responsive support What sets MCP apart is its ability to return images (including diagrams) directly to the MCP client. Users have applied it to search over data ranging from blood tests to patents, and we use…

    2025 · docs.morphik.ai

  22. 22CM

    I use Claude Code across multiple projects with different conventions and some shared repos just as it so happens to be the real world. Managing the config files (.claude/rules/, mcps.json, settings.json) by hand got tedious, so I built a local web UI for it. This one started out as claude-config but migrated to coder-config as I'm adding others (Gemini, AG, Codex, etc). Main features: - Visual editor for rules, permissions, and MCP servers - Project registry to switch between codebases - "Workstreams" to group related repos (frontend + API + shared libs) with shared context -…

    Jan 2026 · github.com

  23. 23

    Codex Plugin: Durable detached local process jobs for Codex

    Jul 2026 · filamentlabs.io

  24. 24SL

    For speech-to-text, large-language-model inference and text-to-speech I created three wrapper libraries in C/C++ (using Whisper.cpp, Llama.cpp and Piper). Follow the URL to see an example that shows how to use these libraries for a speech-to-text, LLM inference, text-to-speech pipeline. Windows and Linux are supported.

    Sep 2025 · github.com

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