原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Attocode Code Intelligence

作者:eren23版本 0.1.26i★ –i在你的电脑上运行
注册名称io.github.eren23/attocode-code-intel

安装

概览

作者提供的说明(英文原文)

Local code search, symbol navigation and change impact for coding agents. No model, no API key.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "attocode-code-intel": {
      "command": "uvx",
      "args": [
        "attocode-code-intel"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add attocode-code-intel -- uvx attocode-code-intel

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "attocode-code-intel": {
      "command": "uvx",
      "args": [
        "attocode-code-intel"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "attocode-code-intel": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "attocode-code-intel"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 eren23 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7212 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7212 个服务器的 95% 更新
  • 基础检查结果等于或优于此分类中其他 7212 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Attocode Code Intelligence 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.26)于昨天进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT3天前更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT20天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT44天前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

attocode-code-intel

Local code search and navigation for coding agents and for people. It runs as an MCP server for Codex, Claude Code, Cursor and other MCP clients, and as a command in your terminal. It needs no model, no API key and no network.

Status: beta. We measured the search quality (see What we measured). We have not shown that it makes agents faster or more accurate.

Quickstart

You need Python 3.12 or later and Git.

uv tool install attocode-code-intel

cd /path/to/your/project attocode-code-intel init

Then restart your agent. init configures Codex, Claude Code and Cursor. Use --client claude, --client codex or --client cursor for one client. Codex needs a trusted project for a project configuration. Claude Code can ask you to enable the project MCP server.

To check the setup, run attocode-code-intel doctor. It starts the configured server, calls two tools and shows the result for each client. The probe also reports the executable and server version returned by that new probe. An already running client session must be checked separately.

For other clients (VS Code, Zed, Windsurf, Claude Desktop and more), run attocode-code-intel install . attocode-code-intel commands lists the targets.

To run the server without an installation, use uvx. This is a configuration for any MCP client that starts a local command:

{

"mcpServers": { "attocode-code-intel": { "command": "uvx", "args": ["attocode-code-intel", "--project", "/absolute/path/to/your/project"] } } }

You can omit --project if the client sends one workspace root. Otherwise the server looks for a repository marker such as .git in the working folder and its parents, but never selects your home folder. If it finds no repository, it stops with an error.

To use the latest source, install from a clone of this repository: uv tool install /path/to/attocode/packages/code-intel.

What your agent gets

Version 0.1.26 gives Rust precision lookups a shared five-second budget and fixes cancelled startup cleanup when a child retains inherited pipes. Other languages keep two seconds; longer reloads still return partial evidence.

Version 0.1.25 uses OpenAI embeddings only when you set ATTOCODE_EMBEDDING_MODEL=openai. Before, an OPENAI_API_KEY in the environment was enough to send code chunks to OpenAI at index time. Rust references are also more reliable while rust-analyzer loads.

Version 0.1.24 adds ATTOCODE_INTEL_RANKING_PROVIDER=openrouter, a preset for the opt-in hosted rerank. In a frozen trial with 24 short questions, the rerank found 24 of 26 labeled files in the first five results, against 20 without it; see Hosted rerank. Rerank stays off by default, because it sends source excerpts to OpenRouter.

Version 0.1.23 is listed in the official MCP Registry and documents a uvx quick start. The opt-in hosted rerank now accepts the dated model ID that OpenRouter returns; see Hosted rerank. Rerank stays off by default.

Version 0.1.22 adds an opt-in discovery budget of up to 100,000 files (ATTOCODE_INTEL_DISCOVERY_MAX_FILES; the default stays 50,000). It also packages the LLM client, so ATTOCODE_FLAG_CONFIDENCE=llm and LLM rule synthesis work from a PyPI install when an OpenRouter or Anthropic key is set.

Version 0.1.21 includes configured search-discovery coverage, OCaml interface parsing and more conservative Go/Rust fallback evidence. The existing 100 ms native budget and 50,000-file discovery safety ceiling remain; bounded fallback is heuristic.

Version 0.1.20 improves native OCaml/Perl call candidates and conservative workspace import candidates for OCaml, Perl and Crystal. Physical paths and ambiguity remain guarded; native limits, ranking and dependencies are unchanged. Optional grammars must be explicitly available before analysis; navigation never downloads them.

Version 0.1.19 restores source text into spare space after fitting a complete compact search page. Existing hits, visible text, source lines and continuations remain protected within the same response budget; ranking and retrieval are unchanged.

Version 0.1.7 also provides changes and trace commands: investigate a diff, follow source-backed caller paths, export JSON/Markdown, and check or refresh saved evidence. MCP equivalents change_context and trace_flow are local full-profile tools. Version 0.1.8 adds exact file/symbol selection and bounded changed-class summaries, with --class-mode expand for class-wide callers. Version 0.1.9 keeps Python docstrings and parameter types, and lists impact results nearest first. Version 0.1.10 shows the best test hit second for "tested" searches, and counts Swift Tests/ folders as tests. Version 0.1.11 counts more test file names as tests, such as _test.dart and Perl .t scripts and t/ modules. Version 0.1.12 makes doctor --client claude read the local-scope entry that claude mcp add writes to ~/.claude.json. Version 0.1.13 fills compact search pages within their budget, offers bounded deeper searches, and repairs stale navigation indexes after successful restart parsing. Version 0.1.18 restores the ready phase after a failed snapshot load is followed by a complete fallback rebuild. Incomplete recovery stays guarded.

Version 0.1.17 lets a later explicit inspection retry a failed selected-file parse after a one-second cooldown, preserving immediate-repeat and source guards. Version 0.1.16 stabilizes tied symbol pages and reduces the Docker image while preserving runtime contracts. It adds bounded online maintenance evidence; the preview and restart experiments did not justify product changes. Version 0.1.15 adds parser ownership by thread, one language-server stderr reader, bounded native recovery without static callers and release install verification on GitHub runners. Version 0.1.14 adds bounded selected-file recovery, safe navigation publication, guarded Elixir definitions and doctor probe identity. See the change investigation guide.

The agent sees 16 tools (the daily profile):

UseTools
Find codesemantic_search, fast_search, search_symbols, bootstrap, relevant_context
Read a symbolinspect_symbol, symbols, cross_references, call_graph
See structuredependencies, explore_codebase, project_summary
Plan a changeimpact_analysis, suggest_tests, review_change
Check the servercapabilities
  • When the agent knows a symbol, inspect_symbol(symbol_name="...", task_hint="...") gives the definition, the source, the references and candidate tests in one call.
  • In an unfamiliar repository, bootstrap(task_hint="...") finds the relevant code and gives a map.
  • impact_analysis and suggest_tests help plan the checks for a change.

For all tools (about 140: rules, security scans, history, snapshots and more), add --profile full to init. The tool catalog lists them. The search details page describes ranking, the response format and the experimental rerankers.

For an experimental local seven-tool surface (0.1.5 or later), use init --profile lean and restart your client. It advertises bootstrap, search_symbols, inspect_symbol, semantic_search, impact_analysis, suggest_tests and capabilities, with conditional routing instructions and 2,000-token responses. Without file watching, notify_file_changed is an eighth tool. Advanced tools require a full-profile session. This opt-in profile has no demonstrated completion benefit; see the completed pilot.

Commands for people

Run these in your project:

attocode-code-intel query "parse config"      # search the code with its own words

attocode-code-intel symbols src/app.py # the symbols of a file attocode-code-intel symbols --search greet # find a symbol by name attocode-code-intel impact src/app.py # the files that a change can affect attocode-code-intel deps src/app.py # what a file imports, and what imports it attocode-code-intel hotspots # the files with the most risk or complexity

Search matches the words of the code and its paths. It does not use embeddings unless you install the semantic extra.

What we measured

  • Search. We ran the 560 issues of Loc-Bench V1, with the full issue as the query. For 53.2% of them, the first five files held all files of the fix (file Acc@5 0.532). On a mix of 10 public benchmarks, file Acc@5 was 0.425. See the first-stage results and the matrix results.
  • Agents. In four studies, Claude Code (Sonnet 5.5) named the files to edit for an issue. The server did not raise file Acc@5. Each run with the server cost 1.4 to 2.1 times as much. When the agent could choose, it seldom called the server. See the agent pilot and study R3.

The R6 review study found no demonstrated review benefit. The completed R7 repair pilot also found no demonstrated benefit; its reviewed decision is to stop expansion. The 2026-10-22 investigation pilot stopped incomplete after its first task pair because structured-output/tool calls failed the frozen protocol. It provides no quality, cost or time benefit evidence.

Limits and troubleshooting

  • First search. The first tool call starts the index build. A search waits up to 15 seconds for the index. On a large repository, a search can report that the index is warming. Then search again. An empty result during warm-up does not prove that the code is absent.
  • Index location. The index is in .attocode/ in your project. When the server makes that folder, it adds a .gitignore, so the index stays out of commits.
  • What the index reads. By default the server discovers at most 50,000 eligible files and skips files over 1 MB. From 0.1.22, the discovery budget setting allows an explicit limit up to 100,000; the selected index can be smaller under its independent file limit. It skips files that .gitignore ignores, and folders that start with a dot. It also skips folders named dist, build, out, output, target, env, tmp, vendor or coverage, and binary, media and lock files. If a build-named folder contains real source, explicitly re-include it with a root .gitignore entry such as !dist/; discovery and edit refresh honor that override.
  • Languages. The base install parses Bash, C, C#, C++, CSS, Elixir, Go, HCL, HTML, Java, JavaScript, JSON, Kotlin, Lua, PHP, Python, Ruby, Rust, Scala, Swift, TOML, TypeScript, YAML a

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