Crabeye Mcp Bridge

io.github.crabeye-ai由 GitHub 帳號 crabeye-ai 發布v1.3.0更新於 Oct 24, 2026

One MCP connection for all your tools — with discovery, namespacing, and execution policies.

已驗證STDIO僅桌面開發者工具安全與監控

概覽

AI 產生的概覽

本機 MCP 橋接器,把所有上游 MCP 伺服器整合到單一 STDIO 連線,只向助理暴露 search_tools 與 run_tool 兩個工具。

可以做什麼
  • 透過 search_tools 與 run_tool 兩個中繼工具,跨所有已設定的上游 MCP 伺服器搜尋並執行工具,不必把全部工具定義塞進上下文
  • 探索、命名空間化並索引 STDIO、HTTP 與 SSE 上游的工具,支援模糊搜尋按需查找
  • 依工具、依伺服器或全域設定執行策略(always、prompt、never)並限制呼叫頻率
  • 以加密憑證儲存庫保存密鑰,主密鑰由作業系統鑰匙圈保護,支援憑證範本,並為 HTTP 上游提供一次性 OAuth 流程
  • 提供命令列工具掃描用戶端設定並注入橋接項目、還原變更,並透過管理程序讓多個橋接共用每個 STDIO 上游的同一子程序
適用情境
當你設定了多個 MCP 伺服器、其工具定義佔滿上下文視窗時適用;也適合需要集中控管哪些工具可直接執行、哪些需核准、哪些被封鎖的情境,以及希望把權杖集中存放在加密憑證儲存庫而非硬編碼在用戶端設定中。
執行需求
以 Node.js 本機程序透過 npx 執行。需要至少一個上游 MCP 伺服器:可執行 init 指令匯入現有用戶端設定,或手動編輯設定檔加入 upstreamMcpServers 區段。僅支援桌面 MCP 用戶端,不支援網頁執行。
安裝前請注意
橋接器可以啟動並執行所有已設定上游伺服器的工具,實際能否執行取決於其策略設定。它要求把權杖等密鑰移入其憑證儲存庫並以範本引用,儲存庫由作業系統鑰匙圈保護的主密鑰加密。init 指令會改寫 MCP 用戶端設定檔,請檢查變更並記得可用 restore 指令還原。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Crabeye Mcp Bridge,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

Crabeye MCP Bridge

One MCP connection for all your tools — with discovery, namespacing, and execution policies.

Every MCP server you add to your AI assistant means another connection, another set of tool definitions injected into the context window, and no way to search or control them centrally. Wire up ten servers with a hundred tools each and your assistant is burning tokens on a thousand tool schemas before the conversation even starts — most of which it will never call.

crabeye-mcp-bridge consolidates all your upstream MCP servers behind a single STDIO interface and exposes exactly two tools to the assistant: search_tools and run_tool. Tools from every server are discovered, namespaced, and indexed as soon as your assistant connects, but none of them touch the context window until the assistant actually searches for them. You can have a thousand tools ready to go without bloating the context, with fuzzy search to find them and per-tool execution policies to control what runs freely, what needs approval, and what is blocked.

[crabeye-mcp-bridge topology: one STDIO connection from an AI assistant to the bridge exposes two tools — search_tools and run_tool — while the bridge fans out to upstream MCP servers like Linear, GitHub, Slack, Sentry, and Figma. Tool schemas stay out of the context window until a search hits.]

Quick start

The fastest way to get started is with init, which discovers your MCP client configs and sets up the bridge automatically:

bash
npx @crabeye-ai/crabeye-mcp-bridge init

This scans for config files from Claude Desktop, Cursor, VS Code Copilot, Windsurf, Zed, Cline, Roo Code, opencode, and Continue.dev, lets you pick which ones to use, and optionally injects the bridge entry. After that, just run npx @crabeye-ai/crabeye-mcp-bridge — no --config flag needed.

opencode and Continue.dev are surfaced as detect-only: their config schemas don't fit the rename-and-inject pipeline, so init prints a manual snippet for them instead of rewriting the file.

To undo, run npx @crabeye-ai/crabeye-mcp-bridge restore.

Manual setup

If you prefer to set things up manually, say your MCP client config looks like this today:

json
{  "mcpServers": {    "linear": {      "command": "npx",      "args": ["-y", "@anthropic/linear-mcp-server"]    },    "github": {      "command": "npx",      "args": ["-y", "@anthropic/github-mcp-server"],      "env": {        "GITHUB_TOKEN": "ghp_..."      }    }  }}

First, store your secrets in the encrypted credential store:

bash
crabeye-mcp-bridge credential set github-pat ghp_abc123

Then rename mcpServers to upstreamMcpServers, add the bridge, and replace hardcoded tokens with ${credential:key} references:

json
{  "mcpServers": {    "bridge": {      "command": "npx",      "args": ["-y", "@crabeye-ai/crabeye-mcp-bridge", "--config", "/path/to/this/file.json"]    }  },  "upstreamMcpServers": {    "linear": {      "command": "npx",      "args": ["-y", "@anthropic/linear-mcp-server"]    },    "github": {      "command": "npx",      "args": ["-y", "@anthropic/github-mcp-server"],      "env": {        "GITHUB_TOKEN": "${credential:github-pat}"      }    }  }}

That's it. Your AI assistant now has access to all tools from all configured servers through a single connection. The bridge automatically excludes itself from mcpServers to avoid recursion, so pointing --config at the same file is safe.

The bridge also reads upstreamServers (shorthand), servers (VS Code Copilot), and context_servers (Zed) as input keys. See docs/configuration.md for the full priority order and self-exclusion rules.

Alternatively, you can add the bridge alongside your existing mcpServers entries without renaming anything — the bridge will pick up the other servers from mcpServers automatically (excluding itself). Disable the other MCP servers in your client so the assistant uses the bridge as the single entry point.

Install as a Claude Code plugin

Register the bridge's repo as a Claude Code marketplace, then install the plugin:

/plugin marketplace add crabeye-ai/crabeye-mcp-bridge/plugin install crabeye-mcp-bridge@crabeye

Claude Code auto-registers the bridge as an MCP server. If you haven't configured upstreams yet, the bridge's startup error will surface in Claude Code's MCP server log — run npx @crabeye-ai/crabeye-mcp-bridge init in a terminal to discover and import existing MCP server configs from your other clients.

Features

  • Discovery + search. Two meta-tools (search_tools, run_tool) instead of N×M tool definitions in context. See docs/how-it-works.md.
  • Configuration. STDIO, HTTP, and SSE upstreams; categories; multi-source config keys. See docs/configuration.md.
  • Authentication. Encrypted credential store, OS-keychain-backed master key, ${credential:key} templates, and a one-shot auth <server> OAuth flow for HTTP upstreams. See docs/auth.md.
  • Policies. Per-tool / per-server / global tool policies (always / prompt / never), rate limiting. See docs/policies.md.
  • STDIO manager. STDIO, HTTP and SSE upstreams routed through a per-user manager process so multiple bridges share a single subprocess or connection per upstream. See docs/stdio-manager.md.
  • CLI. init, restore, credential, daemon, --validate. See docs/cli.md.

License

MIT

來源:README.md,提交 b4268c2

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v1.3.0最新Sep 16, 2026

評分

已滿足適用檢查項的 50%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通25 分

    請保持端點能夠回應 MCP 握手;SourceWeft 每 30 天探測一次。

  • 已宣告認證方式10 分

    請在註冊中心條目中宣告憑證請求標頭,或保持端點能夠回應探測,以便判定其認證方式。

  • 已列出工具15 分

    請讓伺服器在無憑證時回應 tools/list,或發布可在沙箱中無憑證啟動的軟體包。

  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分