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。
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Graphicle

作者:Graphicle-AI版本 0.1.13i★ –i在你的电脑上运行
注册名称io.github.Graphicle-AI/graphicle

安装

概览

作者提供的说明(英文原文)

Code graph and project memory for coding agents, cited to exact files and lines, on your machine.

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 …”。

下载作者的 .mcpb 文件

链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。

在终端中运行这条命令

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。

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 Graphicle-AI 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 7246 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7246 个服务器的 97% 更新
  • 基础检查结果等于或优于此分类中其他 7246 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

Graphicle 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(0.1.13)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 MCPB。

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★ 64,224MIT今天更新
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★ 5,213MIT上个月更新
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。

Code graph and memory for your coding agents, in one Rust program.

Graphicle maps your repository into a code graph, remembers your project's docs, decisions and past agent sessions, and gives your coding agent cited excerpts from both: the exact files and lines. It runs on your machine: no API key needed, no account, no telemetry .

Works with Claude Code · Cursor · Codex · VS Code · Claude Desktop · any MCP client

Quick start · How it works · Benchmarks · Memory, compared · Docs · Coming from Graphify? · Discussions

Graphicle 0.1.11 against Graphify 0.9.100, labelled as in the picture; every measurement and its method are in docs/benchmarks.md . The code-graph engine is a Rust port of Graphify, credited below . Graphicle is not affiliated with Graphify Labs.

From a bug on the screen to a tested fix

Built during Meta's Global AI Developer Hackathon (what was built, and when). With a key for the Meta Model API, graphicle see lets Muse Spark reproduce a bug in a web app with computer use, graphicle pixel finds the code that draws what the model points at, and graphicle fix patches it with a model such as Muse Wonder and runs your tests; when a round fails, the next one reads the failing lines and the files they name. The picture is one live run on excalidraw issue #12053, built from source, and the fix passes excalidraw's own regression test (see it, find it, fix it, check it).

Agent memory, compared

In a pre-release comparison with seven memory systems, Graphicle matched the accuracy of Hindsight 0.10.2 and beat that of Mem0 OSS 2.2.1 (the open-source library, not Mem0's hosted platform) on LoCoMo-10, and while ingesting made about 12 model calls per conversation, against about 160 for Hindsight and 332 for Mem0 (estimates per conversation; each system's total is exact). Labels: development sets; one open model (Qwen3.8-27B) as every system's reader, judge and model; a pre-release build of Graphicle.

SystemLoCoMo-10 accuracy, points [95% CI]Model calls per conversation, ingesting (estimate)Prompt tokens per conversation, ingesting (estimate)
Graphicle (pre-release build)87.7 [85.1, 90.2]1243K
Hindsight 0.10.2, observations on87.3 [85.6, 89.1]1601.14M
Mem0 OSS 2.2.181.9 [79.6, 84.4]3323.18M
MemMachine 0.4.079.6 [77.3, 82.0]23140K
Honcho 3.2.279.2 [76.2, 82.2]2211.25M
Cognee 1.6.369.5 [67.3, 71.2]206291K
Graphiti (graphiti-core 0.30.2)46.5 [44.0, 48.9]1,3634.52M
Mastra Observational Memory 1.36.038.6 [33.6, 43.1]22, and 1 per question356K

On the two other development sets, LME-84 and BEAM-100K, Graphicle trailed none of the systems it was compared with. Every score, with its method and caveats.

Earlier pre-release evaluations also ran three published protocols on GPT models. Under Mem0's own LoCoMo protocol (its prompts, GPT-5 as reader and judge), it scored 93.5%, against 91.6% in Mem0's published result files (paired difference +1.95 points [+0.55, +3.55]). On LongMemEval-S under the same protocol it scored 92.6%, against Mem0's 93.4%. Against Hindsight's published contexts, it tied with a GPT-5.4 reader (LoCoMo 90.4 vs 90.6, LongMemEval-S 94.6 vs 93.4) and with a GPT-4.1-mini reader on LoCoMo (86.4 vs 87.5), and trailed with GPT-4.1-mini on LongMemEval-S (85.8 vs 89.2). Every GPT run, with its labels.

Quick start

brew install graphicle-ai/tap/graphicle

cd your-repo graphicle setup

No Homebrew? curl -fsSL https://github.com/graphicle-ai/graphicle/releases/latest/download/install.sh | sh · Release archives · Other ways to install

Windows: a preview build for x86-64, not yet code-signed (Windows (preview)).

graphicle setup indexes the repository, builds its code graph and connects the coding agents it finds. It also turns on session capture, adds a two-line section to AGENTS.md (unless Claude Code is the only agent) and installs Git hooks that keep the project current. It lists every file it changes and backs each one up first; graphicle disconnect undoes it all.

Then ask your agent to *"use graphicle to find where failed requests are retried"*, or ask from the terminal:

$ graphicle ask "where is tax added to prices?"

Evidence for "where is tax added to prices?" 4 excerpts · 606 of 3,000 tokens

[1] shop/pricing.py:1-7 price_with_tax() """Prices and tax.""" TAX_RATE = 0.2

def price_with_tax(price): """A price with the sales tax added.""" return round(price * (1 + TAX_RATE), 2)

Real output, cut after the first excerpt. With no model configured, ask shows the evidence; graphicle config set model anthropic (or openai , ollama ) adds written answers.

Let your coding agent install it

Paste this into Claude Code, Codex or Cursor:

Install Graphicle with `brew install graphicle-ai/tap/graphicle` (or, without Homebrew,

curl -fsSL https://github.com/graphicle-ai/graphicle/releases/latest/download/install.sh | sh), then run graphicle setup --yes in this repository and list every file it changed.

</details>

Start here

You want toRun
Give your coding agent the code graph and your project's memorygraphicle setup in the repository
Ask a question from the terminalgraphicle ask "how are failed requests retried?"
Browse the graph, the sources and the memorygraphicle open
See what a change to a symbol touchesgraphicle graph extract . --code-only, then graphicle graph affected "retry()"
Check that everything worksgraphicle doctor
Undo everything setup didgraphicle disconnect
Move from Graphify, or run a server for a teamMoving from Graphify · Team server

Why Graphicle

  • Native and fast. One Rust program. On 13 codebases, Graphicle 0.1.11 took 3.4 to 23.9 times less time than Graphify 0.9.100 in 34 of 39 measurements (code-only extract, priming update and update with no change, on one machine with 3 CPUs and 8 workers each); in the other 5, updates with nothing to change, Graphify 0.9.100 now stops early and took less time. The graphs differ slightly: node counts within 1.6%, edge counts within 1.1% ([

只显示了开头部分;其余内容请在仓库中阅读

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